supply chain management
Abolfazl Sadeghian; Seyed Mohammad Ali Khatami Firouzabadi; Laya Olfat; maghsoud Amiri
Abstract
Nowadays attending to closed-loop supply chain matter for survival in competitive circumstances not only has been become a controversial topic but also has been considered as a critical topic too. Close loop supply chain has combined to direct and reverse flow (method/ manner). This paper’s goal ...
Read More
Nowadays attending to closed-loop supply chain matter for survival in competitive circumstances not only has been become a controversial topic but also has been considered as a critical topic too. Close loop supply chain has combined to direct and reverse flow (method/ manner). This paper’s goal is presenting a model for inventory control in closed loop supply chain by multiple objective approach. This research intends to reach it's main goal including reduce expenses such as production, maintenance, transportation in direct flow also decrease the waste material and defective in reverse flow and in conclusion increase the company’s profit by desingning and optimizing multiple objective model. Hence a double purpose model in closed-loop supply chain consists three classes direct flow in which conclude suppliers, manufactures and customers. Furthermore this consists four classes in reverse flow that concludes: collection centers, inspection, repair centers, recycling centers and disposal centers. According to the article’s model, which is multipurpose, linear and integer, At the beginning the model convert to single objective by Weighting and Constraint method and then is solved by using Branch and bound algorithm and Lingo software. Finally, the model extended in Iran Khodro Company as a study case and its function validated. Results and output of model solving demonstrate its capability to be useful for planning and inventory control in closed-loop supply chain.
supply chain management
Akbar Rahimi; mohamad hossein karimi govareshki; Amirreza zareei
Abstract
The competitive landscape among companies and their supply chains necessitates a heightened focus on collaborating with best suppliers and business partners. The appropriate selection of suppliers presents an opportunity for organizations to gain a sustainable competitive advantage while enhancing profitability. ...
Read More
The competitive landscape among companies and their supply chains necessitates a heightened focus on collaborating with best suppliers and business partners. The appropriate selection of suppliers presents an opportunity for organizations to gain a sustainable competitive advantage while enhancing profitability. The Etka organization, responsible for meeting the consumption and general needs of the armed forces, is no exception. Consequently, it requires establishing partnerships with the best suppliers across industries. To address this need, this research aims to provide a framework for selecting suppliers with lean, agile, and resilient approaches within the supply chain of the Etka organization. To achieve this objective, an extensive review of the relevant literature on lean, agile, and resilient supplier selection was undertaken. Through this process, key selection criteria were identified, and the fuzzy screening method was employed to localize and refine these criteria. Furthermore, the combined rough best-worst method was utilized to assign weights to each criterion, reducing uncertainties associated with expert opinions. "Cooperation and coordination" emerged as the most critical criterion from the resilient supply perspective, "trust development" from the agile supply approach, and "product quality" from the lean supply approach. The application of the Rough VIKOR method then facilitated the ranking of selected suppliers, resulting in the Qa'emshahr canning company being identified as the most desirable supplier in the related industry. This study presents a comprehensive framework for selecting lean, agile, and resilient suppliers within the supply chain of the Etka organization, enabling fruitful partnerships that contribute to competitive advantage and overall profitability.
supply chain management
Ali Mirzaei; Esmaeil Mazroui Nasrabadi
Abstract
The supply chain of the food industry is very important for countries. In recent years, occurrences such as floods, frost, heatstroke, shutdown of some layers of the supply chain, cause a ripple effect in the supply chain of food products. The occurrence of disturbances and specifically the ripple effect ...
Read More
The supply chain of the food industry is very important for countries. In recent years, occurrences such as floods, frost, heatstroke, shutdown of some layers of the supply chain, cause a ripple effect in the supply chain of food products. The occurrence of disturbances and specifically the ripple effect can make the country face many challenges, therefore it is necessary to identify and analyze the strategies to deal with the ripple effect. This research has been done in two stages: qualitative (with the aim of identifying coping strategies) and quantitative (with the aim of scenario modeling and analysis). The method of analysis is thematic analysis in the first stage and fuzzy cognitive map in the second stage. The findings show 84 primary codes that were grouped into 21 sub-categories and 4 main categories of "Strategic Management", "Operations Management", "Compilation and Correct Implementation of Laws" and "Supply Chain Management". The analysis of backward scenarios shows the importance of "supplier relationship management", "cooperation and coordination in the supply chain" and "contingency plans", and the analysis of forward scenarios shows the importance of "monitoring environmental changes" and "strategic plan”. Focusing on short-term plans, improving the capabilities of managers in the field of decision-making and problem-solving skills, adjusting supplier selection criteria, improving the design of the supply network based on backup locations, and the existence of safety stock for strategic goods should be the attention of industrialists.
supply chain management
Allahyar Beigi Firoozi; Mohammad Bashokouh Ajirlou; Naser Seffollahi; Ghasem Zarei
Abstract
The current study aimed to cluster the application of digital technologies from Industry 4.0 in the agricultural food distribution network. To achieve this goal, a bibliometric technique was employed to identify prominent trends and themes in this field through the analysis of articles, authors, countries, ...
Read More
The current study aimed to cluster the application of digital technologies from Industry 4.0 in the agricultural food distribution network. To achieve this goal, a bibliometric technique was employed to identify prominent trends and themes in this field through the analysis of articles, authors, countries, and co-citations of authors and bibliographic pairs. Through an extensive search in the Scopus scientific database, bibliographic information for 331 valid and relevant scientific articles was acquired. This information was inputted into the bibliometric package in R software, and the most influential journal, author, university, country, and most cited authors were determined. To visualize the information, Vosviewer software was utilized for co-citation analysis of authors, cited references, and bibliographic pairs. The findings from the network analysis revealed that the studies on the application of digital technologies in the agricultural food distribution network can be categorized into five main clusters.IntroductionIndustry 4.0, viewed as a new industrial stage, has introduced complex information and communication technologies that facilitate comprehensive connections across different parts of the supply chain. The digital technologies associated with Industry 4.0 allow production lines, business processes, and teams within a supply chain to collaborate seamlessly, irrespective of location, time zone, network constraints, or any other factors. Researchers highlight that the advent of digital technologies from the fourth industrial revolution, including radio frequency identification, big data, cloud computing, smart sensors, machine learning, robotics, augmented production, artificial intelligence, augmented reality, the Internet of Things, blockchain, and similar technologies, holds immense potential for significantly enhancing production productivity. These technologies could lead to substantial innovation, competitive growth, and may contribute to improving the sustainability of the current industrial system. To meet the escalating demand for food, agricultural marketing professionals and managers globally must maximize the efficiency of the agricultural distribution network, given the widespread adoption of digital technologies. The increasing significance of this goal has prompted marketing researchers to explore the use of digital technologies in the agricultural food distribution network, leading to a substantial number of studies in this research field since 2011. In this context, the present study aimed to cluster the utilization of digital technologies in Industry 4.0 within the agricultural food distribution network. A bibliometric study was conducted to identify existing gaps in research and propose future directions. The research focuses on the application of digital technologies in the distribution network.Aligned with the research objective, fundamental questions are posed: Which publications, authors, and countries are most influential in the application of Industry 4.0 digital technologies in the agricultural food distribution network? Additionally, what scientific clusters exist in this domain?MethodologyThe objective of the current research is to conduct a bibliographic analysis of studies related to the application of digital technologies in Industry 4.0 within the agricultural food distribution network. Utilizing bibliometric techniques, a crucial measure for evaluating scientific output, a comprehensive examination of scientific literature was carried out concerning the application of digital technologies in Industry 4.0 within the agricultural food distribution network.The search was conducted within the Scopus scientific database, which encompasses a significant array of diverse journals and authoritative articles globally. The search covered three sections: title, abstract, and keywords, yielding a list of studies that exclusively included English-language articles from journals (excluding conference studies and book chapters) published between 2011 (the inception year of Industry 4.0) and 2023. By imposing these criteria, 352 original pieces of data containing bibliographic information were obtained. Subsequently, the title and abstract of each article were meticulously scrutinized to identify information relevant to the agricultural food distribution networks. Among these, 6 articles pertaining to the halal supply chain and 15 articles conducted as systematic reviews were excluded from the bibliographic information collection. The final portfolio for analysis consisted of bibliographic information from 331 articles, which was then entered into the bibliometric software package. This analysis was carried out using R software and VOSviewer software. The bibliometric software package facilitated quantitative bibliographic analysis, while the VOSviewer software was employed for visualizing and analyzing citation networks.ResultsThe quantitative findings indicate a significant increase in studies related to the adoption of digital technologies in the agricultural food distribution network, particularly after 2017. The most widely utilized digital technologies in the food distribution network include blockchain, the Internet of Things, simulation, artificial intelligence, big data, machine learning, 3D printers, sensors, and digital twins.Through the analysis of bibliographic pairs, five primary clusters were identified concerning the application of digital technologies in the agricultural food distribution network. These clusters are associated with the use of digital technologies in ensuring food quality, enhancing distribution network flexibility, establishing modular architecture within the distribution network, implementing intelligent logistics systems, and promoting sustainable distribution networks.ConclusionBased on the themes of the clusters identified in Table 7, it can be concluded that the Internet of Things and blockchain play crucial roles in real-time tracking, tracing, and monitoring of food throughout the supply chain, thereby reducing wastage. RFID technologies and digital twins are highly effective in ensuring food safety and facilitating delivery to consumers, especially in the face of environmental changes and crises such as epidemics. Another application of digital technologies lies in the modular architecture of the food distribution network. Through the use of modular architecture, various technologies can modularize tasks and extensive operations within the food distribution network. Ultimately, all these components can be centralized under blockchain technology, with diverse data stored in a vast cloud space. Consistent implementation of digital technologies in the food distribution network has the potential to establish regional warehouses, resulting in reduced distribution and delivery costs, enhanced food safety and sustainability, and the possibility of customizing food for end consumers. This, in turn, will contribute to the stability of the food network.
supply chain management
Mahsa Pishdar; Atefeh Habibi
Abstract
To explain a framework for managing the risk of transportation in the food industry supply chain, the initial step involves identifying 12 risks that can potentially lead to transportation disruptions, based on the research background. Utilizing the Delphi method and gathering opinions from 15 academic ...
Read More
To explain a framework for managing the risk of transportation in the food industry supply chain, the initial step involves identifying 12 risks that can potentially lead to transportation disruptions, based on the research background. Utilizing the Delphi method and gathering opinions from 15 academic and industrial experts across 3 stages, the risks were ultimately defined. Furthermore, expert opinions were sought to determine solutions to address the identified risks. The grey DEMATEL method was employed to investigate the interaction of risks. The findings revealed that weather problems, natural disasters, insufficient skilled labor/labor strikes, infrastructure capacity, and inflation and exchange rate changes are among the risks that exert a more significant influence on other risks than they are influenced by them. Subsequently, using the grey COPRAS method, the prioritization of solutions to mitigate the identified risks, based on expert opinions, was undertaken. The results indicated that the top-ranked solution is the definition of key performance indicators. Therefore, it is recommended to managers that, in order to establish a robust supply chain and proactively manage risks, they should identify stakeholders and critical processes. Afterward, an agreement on the financial flow in each situation should be obtained, and a value flow map drawn. This approach enables the implementation of preventive measures to reduce supply chain risk and facilitates the preparation of an emergency plan for unforeseen conditions, thereby enhancing resilience.IntroductionDisruption in transportation stands as the pivotal factor undermining the efficiency of the supply chain. Any significant interruption can result in delays or business flow cessation, leading to consequential impacts (Ali et al., 2021). The transportation supply network is susceptible to various technical, economic, and environmental factors (Tan et al., 2023). Simultaneously, research indicates that factors such as a workforce lacking sufficient skills, suboptimal selection of service providers, traffic accidents, and the inability to predict the systemic impact of these risks play a crucial role in transportation, causing disruptions in the flow. In addition to these factors, it is noteworthy that supply chain management in the food industry introduces its own complexities. Unlike other industries, the quality of products in this type of supply chain consistently diminishes during product movement and this issue of perishability intensifying the need for transportation risk management (Hosseini-Motlagh et al., 2019; Choe et al., 2021). Given this context, emphasis should be placed on establishing distribution channels with lower costs and implementing change management to enhance efficiency. However, existing studies have predominantly focused solely on analyzing transportation disruption within companies' supply chains. Clearly, it is insufficient to only address disorders or the risks that may lead to their occurrence. A comprehensive examination of the cause-and-effect relationships among these risks facilitates a systematic understanding of the risk network. This approach enables the development of a more effective program to enhance the resilience of the transportation system. Even in the face of risks and disruptions, this ensures minimal damage, a swift return to normal operational levels in the supply chain, or the application of knowledge management to learn from experiences and prevent the recurrence of disruptions through appropriate implementation solutions. Consequently, the overall performance of the supply chain can be improved. In consideration of these elements, this study aims to address the following main questions:- What are the risks associated with transportation in the food supply chain?- What are the pertinent solutions, according to expert opinions, and what is their prioritization?MethodologyIn terms of its objective, the current study falls within the domain of applied research as it aims to discover practical solutions to address a real-world problem. Regarding information collection, the study is categorized as survey research, wherein data is gathered based on the opinions of 15 experts. Among these experts, 9 are drawn from the industrial community, each possessing over 10 years of experience in the commercial sector and raw material procurement within the food industry. The remaining 6 experts are affiliated with the academic community and have published numerous articles in the field. The study unfolds in several stages. Initially, a compilation of transportation risks causing disruptions in the food supply chain is accomplished through a literature review. Subsequently, the Delphi method is employed to screen and refine these disruptions. The cause-and-effect relationships among the identified disruptions are then scrutinized using the Grey DEMATEL method. Experts are engaged to contribute not only by assessing the risks but also by providing their insights into coping strategies based on their experience. Finally, the coping strategies are prioritized using the Grey COPRAS method.Results and DiscussionAccording to the obtained results, it is evident that the climate problems risks of failure to choose logistics service providers that care about sustainability principles (C6) and frequent change of product delivery time (C9) exhibit the highest degree of interconnectedness with other risks. The weights of these risks have also been determined. Notably, the failure to choose logistics service providers committed to sustainability principles has secured the top rank with a weight of 0.1443. Following closely, the frequent change of product delivery time holds the second position with a weight of 0.1384, while natural disasters rank third with a weight of 0.1039. Turning to coping strategies, it is noteworthy that the solution of "Definition of Key Performance Indicators (KPI)" has claimed the top position. In today's business landscape dominated by Logistics 4.0 and Omnichannel, simplifying processes can create significant added value for any business, particularly in minimizing transfer time. Concurrently, many manufacturing companies are leveraging various logistics transportation modes as a critical factor for promptly responding to demands, thereby enhancing service reliability and minimizing travel time (Foroozesh et al., 2022). The adoption of modern technologies such as the Internet of Things facilitates real-time inventory monitoring, contributing to dynamic pricing policies. As product quality diminishes along the chain, electronic labels enable adjusting product prices based on features (Kumar & Agrawal, 2023).ConclusionStudies indicate that supply chain managers, particularly in food supply chains, have demonstrated significant commitments to sustainability goals, leading to the pursuit of a diverse array of performance improvement projects. This study identifies various risks and corresponding coping strategies. Outsourcing logistics activities to 3PL allows leveraging their expertise in supply chain management, thereby enhancing stability and efficiency. This approach can contribute to reducing the carbon footprint, increasing order fulfillment, and lowering energy consumption throughout the supply chain.For future research endeavors, it is recommended to prioritize strategies related to realizing the circular economy within the logistics system of the food industry. Providing a roadmap for the sustainable development of logistics clusters can enhance supply chain performance, minimize waste, and boost the social credibility of the supply chain. Additionally, attention to the concept of greenwashing in sustainable logistics, particularly concerning the fulfillment of social responsibility, can prove beneficial in improving overall supply chain performance
supply chain management
Mehrdad kiani; davood andalib ardakani; Habib Zare Ahmadabadi; Seid Heydar Mirfakhraddini
Abstract
Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society ...
Read More
Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society and address the environmental and economic challenges related to managing organizational operations. This research aims to analyze the factors enabling the implementation of circular economy and Industry 4.0 in the supply chain of Yazd glass factories. In the initial phase of the research, a review of various articles was conducted using the meta-synthesis method to identify and categorize relevant enablers. This process resulted in the identification of 15 enablers categorized into four dimensions: economic, human resources, organizational management, and infrastructure. In the subsequent step, the Fuzzy DEMATEL technique was employed to examine the cause-and-effect relationships. The findings indicate that, within the economic dimension, the most influential enablers are "budget allocation for the implementation of circular economy and Industry 4.0" and "stimulation of demand for circular products." In the human resources dimension, "training and development of employees" and "organizational culture" play crucial roles. In the organizational-management dimension, "support and commitment of senior management" and "cooperation and networking with supply chain partners (industrial coexistence)" are highly significant. Lastly, within the infrastructure dimension, "development of information technology standards and infrastructures" and "security and protection of intellectual property rights" are considered the most effective enablers for the implementation of circular economy and Industry 4.0 in the Yazd glass factories. The results indicate that the Ardakan glass factories of Yazd should prioritize attention to economic and infrastructural enablers when implementing circular economy and Industry 4.0.
Introduction
The concept of the circular economy can be regarded as a solution to reduce production costs within a sustainable supply chain. In this context, the integration of cyber-physical systems, big data, data mining, data analytics, the Internet of Things, and novel business models can offer significant opportunities for the creation of sustainable industrial value, value capture, and the promotion of the circular economy (Antikainen et al., 2018). Industry 4.0, often referred to as the future of supply chains, can have numerous implications for sustainability, including the optimal utilization of resources and technology (Quezada et al., 2017). Based on the sustainability axis, the concept of Industry 4.0 aids industrial managers in encompassing not only environmental protection and control initiatives but also aspects of process safety, such as resource efficiency, human resource and societal well-being, and the development of smarter and more flexible supply chain processes (Luthra & Mangla, 2018). Numerous studies have explored the factors that impact the implementation of circular economy and Industry 4.0, and these factors have been broadly classified into categories such as barriers, challenges, drivers, and enablers (Fedotkina et al., 2019). Identifying the enablers that are effective in implementation is a crucial step in enhancing the performance of a circular and intelligent supply chain. Until these enablers are identified, it is impossible to determine their relative importance. Following their identification, industry practitioners and policymakers can develop appropriate strategies for their implementation. As such, this current research aims to identify, categorize, and analyze the effective enablers for implementing circular economy and Industry 4.0 at the Ardakan Glass Factory in Yazd, which is the largest glass factory in West Asia. To achieve this, both a qualitative method for enabler identification and the technical Dimtel method using fuzzy logic for establishing cause-and-effect relationships between enablers are employed. What sets this research apart from others is its focus on identifying the combined enablers for implementing the circular economy and Industry 4.0 at the Ardakan Glass Factory Group of Yazd, as well as the network approach that examines the relationships and interactions between these enablers. Given these key elements, this research aims to address the following questions:
-What are the effective enablers for implementing the circular economy and Industry 4.0 at the Ardakan glass factories in Yazd?
-What is the effectiveness and influence, including cause-and-effect relationships, of these enablers?
Materials and Methods
This research is categorized as applied-developmental research in terms of its purpose and is classified as a field-library study in terms of its methodology. Its objective is to formulate a novel scientific model of enablers for implementing circular economy and Industry 4.0 within organizational supply chains. Given the significant number of qualitative articles that have explored the enablers of Industry 4.0 and the circular economy across various industries and the need to establish a shared understanding of these enablers, the first stage of this research involved identifying effective enablers using the meta-synthesis qualitative method. Their validity was assessed through content validity, which involved obtaining opinions from 15 organizational experts. In the second phase of the research, the researchers evaluated the effectiveness and impact of these enablers using the Fuzzy DEMATEL method. The statistical population for the first stage of the research comprised all studies published in the Scopus database, the largest text database, related to the enablers that influence the implementation of circular economy and Industry 4.0 within organizational supply chains up until the commencement of this research. In the second stage of the research, the statistical population included all professors and managers with expertise in sustainability, familiar with circular economy, and knowledgeable about Industry 4.0 technologies at Ardakan Glass Factories in Yazd. For this phase, a purposeful sampling method was used to select ten participants.
Discussion and Results
The purpose of the current research is to analyze the enablers that are effective in implementing the circular economy and Industry 4.0 within the supply chain of Ardakan Glass Factories in Yazd. In the first stage of the research, various articles were reviewed, and the meta-combination method was employed to identify and categorize relevant enablers. This process led to the identification of 15 enablers across four dimensions: economic, human resources, organizational management, and infrastructure. In the second stage, the Fuzzy DEMATEL technique was utilized to investigate the cause-and-effect relationships between these enablers. The research results revealed that the economic and infrastructural enablers are considered influential dimensions that affect human resources and organizational management dimensions. Within the economic dimension, "budget allocation for the implementation of the circular economy and Industry 4.0" and "stimulation of demand for circular products" emerged as the most effective enablers. Additionally, in the infrastructure dimension, "development of IT standards and infrastructure" was identified as the most influential enabler for the implementation of the circular economy and Industry 4.0 within the supply chain. In the organizational management dimension, "the support and commitment of senior management" was recognized as the most influential enabler.
Conclusion
While the enablers mentioned are considered among the most effective ones in implementing circular economy and Industry 4.0 in the Ardakan Glass Factories of Yazd, it's crucial for the glass industry to prioritize the most important enablers. It's essential to pay adequate attention to all identified enablers. Using specific guidelines and a checklist of effective enablers during decision-making can facilitate the decision-making process and enhance decision-making capabilities. Therefore, based on the identified enablers and their importance in this research, it's recommended to develop and provide guidelines and checklists for executive managers. Among the significant limitations of this research is the reliance on a single scientific database, Scopus, for sourcing research. It's advisable to supplement this by utilizing other databases such as Google Scholar and Web of Science. Additionally, the classification of enablers was conducted using a qualitative approach. Researchers are encouraged to name and categorize enablers using survey and quantitative methods, such as cluster analysis, to expand their research scope. Another limitation pertains to the research's statistical population, which was restricted to Ardakan Glass Factories in Yazd due to time and cost constraints. To generalize the research results, it's advisable to investigate the same research topic in other glass factories across the country. Future researchers could employ methods like fuzzy cognitive mapping and systems dynamics to examine relationships and interactions between enablers. Moreover, the enablers identified and analyzed in this research were primarily based on international studies. To adapt these enablers to the specific conditions of Iran's industries, it's suggested that in-depth interviews be conducted with industry owners. This way, certain enablers that may be unique to Iran's circumstances or require different interpretations can be revised.
supply chain management
Fatemeh Arjmandi; Parvaneh Samouei
Abstract
Planning and scheduling operating rooms and required equipment is very important for hospital managers from the perspective of cost, social, and health principles. Because operating rooms are one of the sources of income for hospitals that can provide the services needed by emergency patients who arrive ...
Read More
Planning and scheduling operating rooms and required equipment is very important for hospital managers from the perspective of cost, social, and health principles. Because operating rooms are one of the sources of income for hospitals that can provide the services needed by emergency patients who arrive randomly and elective patients whose surgery is preplanned. Since some tools used in operating rooms need to be sterilized each time, and in the real world, due to various reasons such as the physical condition of each patient, the duration of surgeries is uncertain, in this research, as well as considering the uncertainty of surgery times for emergency and elective patients, a robust scenario-based integrated mathematical model with two objective functions is presented. In this model, in addition to minimizing the cost of operating rooms, sterile section, and penalties for delay in surgery, the competition time of the last operation is minimized. Solving several problems and different sensitivity analyses confirmed the validation of the presented model from the viewpoint of the hospital managers.
Introduction
The healthcare system is one of the most important topics that has attracted the attention of researchers and hospital managers. Two significant elements of healthcare systems are patients and hospitals, and their planning and scheduling are necessary for providing better services. Hospital managers aim to minimize costs or maximize profits while considering service times. Operating rooms are often the most critical sections of the hospital. Since life and death issues are at stake in the operating rooms, even the slightest delay or lack of resources can endanger human lives. Therefore, careful planning and scheduling of operating rooms and their resources is especially important. Additionally, to prevent potential hospital infections, the sterilization of reusable medical instruments is essential for every operation. Furthermore, patients can be broadly categorized into two groups: emergency patients who arrive randomly, and elective patients whose surgeries are preplanned. Planning and scheduling operating rooms, along with the required equipment, is of utmost importance for hospital managers, taking into account cost, social factors, and health considerations. Some items used in operating rooms need to be sterilized after each use, which incurs both time and cost.
Methodology
Due to high fluctuations of the duration of surgery, the different condition of each patient, and in order to get as close as possible to the real conditions, the duration of each surgery is considered uncertain. In this research, in addition to considering selected patients, considering the uncertainty of the duration of surgery, emergency patients have also been investigated, and dealing with uncertainties, the robust optimization approach is used. This approach is stable against changes, and minimizes the fluctuation of changes and maintains optimal and feasible. Therefore, in this research, as well as considering the uncertainty of surgery times for emergency and elective patients, a robust scenario-based integrated mathematical model with two objective functions is presented. In this model, in addition to minimizing the cost of operating rooms, sterile section, and penalties for delay in surgery, the competition time of the last operation is minimized. There are costs for performing elective and emergency operations, and in order to give priority to emergency patients, the cost of performing the operation of these patients is lower than the cost of performing elective operations surgeries of emergency patients, such as those injured in accidents, must be performed as soon as possible and these patients should be paid less. Also, for emergency patients, a maximum waiting time is considered, which they should not wait more than it. Obviously, surgeries that cannot be scheduled during the working hours of the operating room are postponed. Every patient needs a number of reusable medical tools that require sterilization. The sterile duration of reusable tools and the capacity of each sterile machine are known.
There are various techniques for solving multi-objective problems, one of which is the epsilon constraint method. In this method, one of the objective functions is considered as the main objective function and other objective functions are applied as constraints to the problem. Various developments for the epsilon constraint method have been presented to make it more efficient, among which we can mention the Augmented Epsilon Constrain (AEC) method. Moreover, in order to solve the bi-objective integrated mathematical model, Mulvey's robust method is implemented on the model, and its validation is carried out in the GAMS software with the AEC method.
Results and Conclusion
Different sensitivities all confirm the validity and accuracy of the model from the point of view of hospital managers. According to the obtained results, the changes of the three parameters of surgery delay cost, duration of surgery and sterile duration times have more effects on the both objective functions of the mathematical model than other parameters of the problem. Furthermore, the obtained results show that the first objective function, which includes the total cost, will have the highest value when the delay cost parameters and the duration of the surgical operations increase. For the second objective function, which shows the complete time of the last operation, the most challenging situation occurs when the parameters of the duration of surgical operations and the sterile duration increase. Therefore, the most ideal situation from the point of view of the hospital manager is to reduce all three parameters, which will reduce, the total cost and the completion time of the last operation; Moreover, the results show, the separate costs of planning and scheduling of the operating room and the sterile department are more than when the planning and scheduling of the operating rooms and the sterile department were examined in an integrated manner. The results of this research can be used for the integrated planning and scheduling of the operating rooms and sterilization department in all hospitals as a suitable management tool.
supply chain management
shahryar marzban; Morteza Shafiee; Mohammad Reza Mozaffari
Abstract
There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, ...
Read More
There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, we aim to assess the sustainability of the supply chain for perishable products in the food industry. After examining both external and internal factors and identifying a research gap, the structure of the present study involves a four-stage supply chain. Input and output variables were selected based on perishable products and the three dimensions of sustainability. To achieve this goal, we conducted field and library studies to identify and extract relevant input, output, and intermediary indicators for evaluating the relative efficiency of supply chains in various sectors. Subsequently, we examined the supply chain's efficiency and ranked the efficient units. Given the primary focus on perishable materials, our study involved 18 dairy and meat factories in Fars province as the statistical population. We utilized WinQSB software to analyze network downtime and to model and solve the data. The results highlight that the most significant challenges faced by the companies are in the supply sector. Based on these findings, we provide recommendations for companies to enhance their performance.IntroductionIn the food industry, there are numerous inventory systems that deal with perishable items, which have a limited shelf life. These perishable items encompass a wide range of products, including food, fruits, and medicine. Given the extensive use of these products, it is crucial to model perishable products within a supply chain context. Furthermore, reviewing the contracts and regulations among the supply chain members is of great importance for decision-making in interactive conditions. This study aims to determine the most effective ordering policies at different levels of the perishable food supply chain. The goal is to maximize the overall profit of the chain while minimizing social and environmental negative impacts. Our supply chain consists of four levels, including suppliers, manufacturers, distributors, and retailers. We have thoroughly investigated the dimensions of sustainable development, ultimately leading to an assessment of the overall performance of the chain. The primary research question we seek to answer is: 'How does the performance of the perishable product supply chain align with a sustainable development approach?MethodologyIn this section, we employed the network data overlay analysis model to assess the performance of the research supply chain and determine the efficiency of the research units, with a particular focus on perishable products. Conventional Data Envelopment Analysis (DEA) models typically overlook the steps and internal processes within Decision-Making Units (DMUs). These conventional DEA models treat each company as a DMU and limit their calculations to initial inputs and final outputs. Given that DEA has been increasingly used in recent years for buyer-seller relationships, production-distribution processes, and performance evaluations in supply chains, and recognizing that a supply chain is a unique decision-making unit with not only input and output indicators but also intermediary indicators that flow from one stage to the next, traditional data envelopment analysis models may fall short in accurately and comprehensively evaluating supply chain performance due to the network or multi-stage nature of the supply chain. Hence, this study adopts the NDEA model with a fresh approach, calculating efficiency based on sustainability indicators related to perishable products in 18 manufacturing supply chains of dairy, meat, and protein products. Conducting an in-depth study to identify the significant parameters in the research field is a prerequisite for any applied research. To this end, we conducted extensive field and library research to investigate variables and indicators across various supply chain activities. This allowed us to identify and extract meaningful input, output, and intermediate indicators for evaluating supply chain performance in the supplier's sector. After reviewing existing literature, we identified 51 specific indicators that play a crucial role in the research.ResultsAccording to research findings, it is shown that the average efficiency of the supply chain for the production and distribution of perishable products in the financial year studied by the research was 0.9634% in the suppliers' sector. This average was 0.9899 in the producers' sector, 0.9903 in the distributors' sector, and 0.9707 in the retailers' sector. Therefore, the average efficiency indicates that the most significant inefficiency problems of the studied companies are related to the supplier sector. Furthermore, the overall average efficiency is 0.9950. According to the results obtained from the Anderson-Piterson Method for Employer Units Ranking, DMU3's Supply Chain demonstrates strong efficiency, and the supply chains of DMU7, DMU2, and DMU4 followed in the subsequent rankings. All supply chains were rated based on efficiency.ConclusionAmong the supply chains of the 18 companies studied in the research that deal with perishable products, the supplier process exhibits lower efficiency scores compared to the production, distribution, and sales processes. Consequently, it is recommended that inefficient companies at each stage take action to identify the factors causing inefficiency in the production, distribution, and sale processes of perishable products. This can be achieved by modeling the performance of efficient companies, with the goal of improving the efficiency at each stage and overall efficiency. Based on the model and research results, the following topics are suggested for future research: Given that most of the inefficiency is associated with the first stage of the model, it is advisable to pay greater attention to the supply of raw materials and transportation, or to select different input indicators. The supply of raw materials for factories emerged as one of the major challenges in this research, highlighting the inefficiency at the first stage. It is recommended that separate modeling be conducted to address the supply of raw materials in the food industry. The highest inefficiency in the fourth stage of the model is attributed to the limited consideration of the social dimension in sustainable development. For future research, it is suggested to focus more on social dimension indicators, such as satisfaction, motivation, empowerment, respect, mutual trust, social commitment, and the creation of suitable working conditions, as well as workers' health and safety. Regarding the inefficiency in the second stage (manufacturers), future research could explore strategies to enhance the freshness of raw materials and the shelf life of perishable products. For the inefficiency in the third stage (distributors), future research should concentrate on modeling and designing innovative distribution systems and routing for perishable products.
supply chain management
Mina Kazemi Miyangaskari; Mohammad Reza Mehrregan; Hossein Safari; samira keivanpour; Mahmoud Dehghan Nayer
Abstract
In today's competitive business landscape, the efficient management of supply chains has become a cornerstone of success for economic enterprises. Supplier selection, as the initial link in the supply chain, holds significant sway over various critical factors, such as product quality, return rates, ...
Read More
In today's competitive business landscape, the efficient management of supply chains has become a cornerstone of success for economic enterprises. Supplier selection, as the initial link in the supply chain, holds significant sway over various critical factors, such as product quality, return rates, and production costs. However, the real world is rife with uncertainties, making the application of a fuzzy approach highly advisable. This study's primary objective is to develop a model for supplier selection and order quantity determination for perishable protein products in a retail setting under uncertain conditions. Initially, a comprehensive fuzzy multi-objective model is designed for Kourosh Protein, a company in the closed-loop supply chain, aiming to minimize costs, waste, and maximize profit, customer satisfaction, quality, and profit margin in the face of uncertainty. Subsequently, this full-fledged fuzzy multi-objective model is transformed into a deterministic single-objective model using the Sharma and Agarwal method (2018), yielding optimal order quantities from each supplier. The model's practical implementation in an Iranian retail store for protein products, such as sausages, bologna, hamburgers, etc., demonstrates its potential to reduce costs and boost profits.IntroductionThe global population's rapid expansion and shifts in lifestyle have significantly elevated the food sector's importance in the global economy, specifically in Sustainable Food Supply Chain Management (SFSCM). SFSCM plays a pivotal role in balancing economic, social, and environmental criteria to optimize supply chain performance. Within the complex food supply chain, suppliers wield considerable influence due to their impact on product attributes, safety, quality, and perishability. Supplier selection, a critical facet of SFSCM, substantially affects a company's strategic and operational performance, product pricing, and quality. In this context, this research introduces a fully fuzzy multi-objective model (FFMOP) to enhance the sustainable supply chain performance of a retail company's protein products. Given the inherent uncertainties associated with supplier selection, the proposed model incorporates an extensive array of variables to simulate real-world scenarios. This innovative approach aims to address identified gaps in existing literature, providing a more robust and realistic tool for bolstering supply chain sustainability.Materials and MethodsThis study constructs a full fuzzy multi-objective model with the objective of determining optimal order quantities within the food supply chain while integrating sustainability criteria. The analyzed supply chain network encompasses multiple suppliers, a single retailer, and end consumers, characterized by multi-product and multi-level interactions. The model seeks to optimize profit, customer satisfaction, brand acceptance, quality, profit margin, and minimize waste production while determining the optimal order volume for each product from each supplier. Reviewing the existing literature reveals various approaches to tackle Full Fuzzy Multi-Objective Problems. This research employs the methodology proposed by Sharma & Aggarwal in 2018 to solve the FFMOP model. After defuzzification, the final model is solved using GAMS software to determine the optimal values of decision variables.ResultsThis research utilizes a case study of an Iranian retail company with eight main suppliers providing 15 protein food products. However, the focus is primarily on four key products: sausages, bologna, hamburgers, and pizza cheese, which are examined. Data for the study was collected from historical company records and interviews with experts from June 2021 to 2022. Model parameters are defined using trapezoidal fuzzy numbers. A comparison of optimal order quantities with the company's actual orders and sales reveals that the proposed model for order allocation leads to reduced ordering, maintenance, and procurement costs for the company. Additionally, the model mitigates waste resulting from unsold products.ConclusionSupplier selection stands as a pivotal process in an effective supply chain, exerting substantial influence on a company's strategic outcomes and performance metrics. This study employs a full fuzzy multi-objective model to identify the most suitable supplier and determine optimal orders within a sustainable food supply chain context. To better mimic real-world conditions, variables and parameters are treated as trapezoidal fuzzy numbers. A comparison of the model's outputs with actual sales data indicates that this methodology aligns more accurately with sales figures. Consequently, applying this model has the potential to reduce waste production and economic consequences. The study's achievement lies in selecting a supplier through a methodology that simultaneously considers sustainability criteria within a fully fuzzy environment while determining optimal order quantities from various suppliers. Moreover, the model's flexibility allows for its application across diverse industries, including dairy and dried fruit, for procuring and selling an array of products from potential suppliers.
supply chain management
S.Ali Torabi; Yasin Heidari
Abstract
In a competitive world, one of the most crucial ways to enhance the supply chain performance of manufacturing companies is through integrated scheduling of production and distribution activities. Two significant concerns for dentists and patients include delayed denture deliveries and the multiple production ...
Read More
In a competitive world, one of the most crucial ways to enhance the supply chain performance of manufacturing companies is through integrated scheduling of production and distribution activities. Two significant concerns for dentists and patients include delayed denture deliveries and the multiple production and correction processes for dentures. This research addresses these concerns by developing a mixed-integer linear programming model for solving the integrated production and distribution scheduling problem in a fixed denture supply chain operating under an additive manufacturing environment. The objective functions of this model aim to minimize the cost of production and distribution orders while reducing weighted delays. The Augmented Epsilon Constraint Method is employed to identify Pareto-optimal solutions. To validate the mathematical model, a numerical example and a case study are presented, and various sensitivity analyses are conducted on key model parameters. The numerical results demonstrate substantial improvements in total costs and customer satisfaction levels.IntroductionA supply chain (SC) comprises several interconnected echelons and processes, where an integrated perspective can lead to optimal overall SC performance. Simply improving an organization's internal processes is insufficient for competitiveness in the market; establishing effective relationships with suppliers, distributors, and other SC stakeholders is essential. Achieving maximum value along the SC involves focusing on cost reduction through cost-effective decision-making. In the past decade, the rising adoption of 3-D printing and additive manufacturing technologies in SCs, as a prominent disruptive technology in the Industry 4.0 era, has created numerous opportunities for improving manufacturing SCs compared to traditional production methods. These opportunities include reduced setup and production times, lower safety stock levels, and fewer processing steps. Additive manufacturing has found applications in various fields, particularly in denture production. This research addresses two primary concerns in the field: timely denture delivery and the multiple production and correction processes associated with dentures. A novel mathematical model is developed to tackle these issues, aiming to solve the integrated production and distribution scheduling problem in a fixed denture supply chain operating within an additive manufacturing environment. The objective functions of this model aim to minimize the costs associated with production and order distribution while minimizing the weighted total delays.Materials and MethodsA mixed-integer linear programming model is devised to address the problem outlined in this paper. The Augmented Epsilon Constraint Method is applied to identify Pareto-optimal solutions. To validate the mathematical model, a numerical example and a case study are presented, and several sensitivity analyses are conducted on key model parameters to elucidate their critical roles in the final solutions.Discussion and ResultsA case study is provided to demonstrate the practical applicability of the developed model. Sensitivity analyses on demand data highlight the substantial impact of demand management on final solutions. This research presents a two-objective optimization model to address the simultaneous scheduling of production and order delivery in a three-tier dental prosthesis supply chain. The first tier comprises a dental prosthesis production laboratory, while the second and third tiers include distributors and dentists (final customers). The objective functions include the minimization of total order delivery costs and the average weighted lateness of delivered products from a fixed dental prosthesis production laboratory. Constraints encompass delivery time delays, order allocation to customers, capacity limitations, calculations of time to reach each customer, and vehicle routing. Given that this research problem falls into the category of multi-objective problems, the Augmented Epsilon Constraint Method is employed to obtain Pareto-optimal solutions. To investigate and implement the proposed model, a fixed dental prosthesis production laboratory in Neka City is examined. The numerical results indicate the existence of a trade-off between the problem's objectives.ConclusionsThis paper presents a bi-objective model to address the integrated production and distribution scheduling problem in a three-tier dentures supply chain, aiming to minimize total delivery costs and the average weighted tardiness. The first tier includes a dentures production laboratory, while the second and third tiers comprise distributors and dentists, respectively. Numerical results based on a real case study demonstrate the practical applicability of the model. Several avenues for future research include considering uncertainty in input data and developing efficient meta-heuristic algorithms for solving large-scale instances.
supply chain management
hossein karimi; MohhamadJavad Jamshidi; Milad Bakhsham
Abstract
This research aims to identify key components and indicators for managing green supply chains utilizing the Internet of Things (IoT). The methodology employed is a mixed approach consisting of two stages. First, through qualitative content analysis, this study reviews theoretical foundations and previous ...
Read More
This research aims to identify key components and indicators for managing green supply chains utilizing the Internet of Things (IoT). The methodology employed is a mixed approach consisting of two stages. First, through qualitative content analysis, this study reviews theoretical foundations and previous research to identify indicators associated with drivers for green supply chain management based on IoT. Subsequently, these indicators were presented to 22 experts in management and information technology to validate and verify them. The research findings reveal that the IoT-based green supply chain model encompasses nine components and 66 indicators. These components include intelligent supply chain management, real-time monitoring of object statuses in the supply chain, intelligent object transfer along the supply chain, intelligent object location in the supply chain, information transparency within the supply chain, corruption reduction, intelligent quality management within the supply chain, intelligent sourcing in the supply chain, intelligent distribution management, and intelligent inventory management. The comprehensive drivers in the proposed model emphasize the importance of incorporating IoT in supply chain management to enhance overall supply chain performance while addressing environmental concerns.IntroductionAs technology continues to advance rapidly across various industries, mankind has enjoyed an improved quality of life. However, the environmental toll of recent decades, such as global warming, water scarcity, polar ice melting, habitat destruction, and deforestation, has raised significant environmental concerns. Modern human activities have contributed to these environmental issues. Consequently, there is mounting pressure on companies to integrate environmentally responsible practices into their operations and supply chains. Recognizing the pivotal role of green supply chain management in sustainable job creation, environmental problem reduction, improved public health through safer food consumption, and enhanced agricultural land productivity, recent years have witnessed increased interest and research into the determinants of green supply chain management.MethodologyThis research adopts a mixed-method approach conducted in two stages. Firstly, qualitative content analysis is employed to review theoretical foundations and prior studies, facilitating the identification of indicators associated with drivers for green supply chain management using IoT. Subsequently, these identified indicators are validated and verified by 22 experts specializing in management and information technology.ResultsThe research findings indicate that green supply chain management, with an IoT approach, comprises nine components: intelligent supply chain management, real-time monitoring of object statuses, intelligent object transfer, intelligent object location, information transparency, corruption reduction, intelligent quality management, intelligent sourcing, intelligent distribution management, and intelligent inventory management.ConclusionsThis study highlights the presence of nine components and 66 indicators within the IoT-based green supply chain model. These components encompass various aspects of supply chain management, emphasizing the importance of incorporating IoT technology to enhance overall supply chain performance while addressing environmental considerations. Due to the growing concerns surrounding environmental issues and the emission of harmful substances by companies, it is highly recommended to incorporate the IoT into supply chain management. This integration serves to monitor and control the quantity of waste generated, and encourages the use of environmentally-friendly 3D printing for creating IoT sensors instead of traditional plastic materials. Furthermore, it is advisable to optimize waste collection schedules and routes for garbage trucks, as these measures can significantly reduce the time and resources spent on waste management. To facilitate this transition, managers should organize in-service training programs to educate employees about IoT technology and communication equipment, emphasizing the positive impact of these advancements on green supply chain management. Additionally, adopting state-of-the-art technologies like Radio-Frequency Identification (RFID) in supply chain systems can contribute to the development of a sustainable and environmentally-conscious supply chain. Legislative bodies should also play a crucial role in promoting green supply chain practices by identifying and addressing legal loopholes in existing supply chain-related laws. This can be achieved through the implementation of incentives, such as tax reductions for eco-friendly companies, or penalties, including tax hikes, financial fines, and even legal repercussions, to encourage the adoption of smoother and more environmentally responsible supply chain management practices. It's worth noting that this research has certain limitations. It primarily relied on articles within specific databases during a defined timeframe, excluding other valuable sources like foreign books and theses due to accessibility constraints. Furthermore, qualitative research inherently depends on the researcher's interpretation and perspective, potentially affecting the reliability of the results. Lastly, challenges related to the COVID-19 pandemic and respondent reluctance posed difficulties during the research process.
supply chain management
mona mousavie; Mahmoud Moradi; Mostafa Ebrahimpour Azbari
Abstract
In light of the continuous and rapid changes in global competition, companies face the imperative of consistently introducing new products or expanding their existing product lines to maintain their competitive edge. Recognizing that numerous factors within the supply chain influence the production, ...
Read More
In light of the continuous and rapid changes in global competition, companies face the imperative of consistently introducing new products or expanding their existing product lines to maintain their competitive edge. Recognizing that numerous factors within the supply chain influence the production, design, distribution, and introduction of new products, understanding supply chain risks is crucial, spanning from the procurement of raw materials to the delivery of products to the market. Consequently, risk management stands as one of the most critical challenges within the supply chain, significantly impacting New Product Development (NPD) performance. This research seeks to answer the primary question: "How and to what extent do various supply chain risks affect newly developed products?" While prior research has employed various methods to evaluate and manage supply chain risks, few models have explored the interplay of these risks on each other and their influence on performance dimensions. In this study, based on a review of theoretical foundations and prior research within the clothing manufacturing sector, we identified dimensions of newly developed products and supply chain risks. We employed the Delphi technique through interviews to identify the most significant risks. Subsequently, we employed the Cross-Impact Analysis method to elucidate relationships between these factors. Finally, we utilized Bayesian networks to analyze the impact of identified risks on the performance of the selected new product, conducting sensitivity and scenario analyses. The findings indicate that environmental and supply risks are more likely to manifest than other risks, with three operational, distribution, and demand risks, influenced by environmental and supply risks, exerting the most direct impact on new product performance, particularly in the dimension of quality.IntroductionModern organizations recognize that traditional competitive strategies, such as improving quality and reducing costs, no longer suffice to remain competitive. Research has demonstrated that numerous new product development NPD projects face failure for various reasons. Effective risk identification and management, particularly concerning supply chain risks in NPD projects marked by a high degree of uncertainty, emerge as pivotal factors for NPD success. In this context, the clothing sector, characterized by a complex supply chain structure, has been extensively studied. However, prior research has predominantly examined existing risks individually, overlooking the interactions between risk components and their simultaneous effects on one or more project objectives. In this research, we not only assess the simultaneous impact of risks on product performance using the Bayesian network method, an effective approach in supply chain risk analysis, but also investigate the severity of risk impacts under different scenarios. This research addresses three primary objectives:Identification of supply chain risks in the clothing industry based on background research and case studies.Determination of interdependencies among variables using conditional modeling.Evaluation of the influence of supply chain risks on new product performance using the Bayesian network method under varying scenarios.Literature reviewNumerous researchers have investigated supply chain risks and their repercussions on product and organizational performance. Asgharenjad Nouri et al. (2021), in their article titled "The Effect of Risk Management on New Product Development in the Banking Industry," explored the impact of various risk indicators on new product development. Their results underscore the significant positive influence of managing all risk indicators, including technology, market, environment, finance, organizational resources, and commercialization, on new product development. Qazi et al. (2017), in their article titled “Supply Chain Risk Network Management,” prioritized risks and corresponding strategies through a case study involving semi-structured interviews. They initially identified organizational performance criteria and then linked them to relevant risks, using a matrix of expected profit to investigate the impact of risks on specified performance criteria. Subsequently, they employed the "weighted net evaluation" method to assess practical strategies.MethodologyIn conducting this research, we initially extracted supply chain risks and product performance dimensions from the existing literature. Subsequently, we employed the Delphi technique to select the most significant supply chain risks, providing indicators to participating experts through questionnaires with a 5-point Likert scale. We then used the Content Validity Ratio (CVR) index to confirm or reject the components derived from the questionnaires. In the next step, we used the Cross-Impact Analysis method, employing pairwise comparisons via questionnaires, to reveal relationships between the key risk criteria. Finally, we investigated the impact of identified risks on the performance of the selected new product within the supply chain of Happy Land factory using the Bayesian network method under various scenarios.Discussion and ResultsThe results from the Bayesian network analysis in this research demonstrate that environmental risk, as an external risk within Happy Land’s supply chain, exerts the most significant influence at the highest level of the Bayesian map. Subsequently, other risks, including economic risks, supplier risks, distribution risks, operational risks, and demand risks, are categorized in subsequent levels. Additionally, sensitivity analysis scenarios, depicted in the Tornado chart, reveal that supply chain risks have a substantial impact on performance criteria. According to this scenario analysis, the primary risk affecting quality and cost target nodes is operational risk, while the major risk affecting the product delivery time node is distribution risk, and the primary risk influencing profitability is demand risk. Results from both pessimistic and optimistic scenario analyses under the second scenario of the research indicate that in the pessimistic state, the presence of a high percentage of these risks significantly negatively impacts quality performance. Conversely, in optimistic scenarios, where these risk factors are not present, improvements in quality's functional dimension exhibit the most substantial impact.ConclusionWhen introducing a new product to the market, evaluating and managing supply chain uncertainties is essential due to the mutual influence of new product development and the supply chain. Supply chain risk management, which commences with the accurate identification and assessment of risks and proceeds with appropriate responses, is crucial for providing efficient and effective new products to the market. In addition to employing the Bayesian network method, a highly effective tool in supply chain risk analysis, we have endeavored to evaluate the simultaneous impact of risks on product performance and assess the severity of risk impacts under various scenarios, including optimistic, pessimistic, and sensitivity analyses. Scenario building proves to be an effective method for validating a developed model to measure the impact of risks under different conditions on target criteria.
supply chain management
Homa Abedi Dehkordi; Ghasem Tohidi; Shabnam Razavyan; Mohammad Ali Keramati
Abstract
Cement production in Iran takes place across various geographical locations, each characterized by distinct weather conditions. The technology employed in cement production varies depending on the availability of raw materials, fuel sources, and essential resources like water. Consequently, diverse inputs ...
Read More
Cement production in Iran takes place across various geographical locations, each characterized by distinct weather conditions. The technology employed in cement production varies depending on the availability of raw materials, fuel sources, and essential resources like water. Consequently, diverse inputs and outputs assume significance in each production technology, resulting in non-homogeneity among cement factories. Despite these differences, all these facilities are engaged in cement production, warranting a comparative analysis of their efficiency. This study examines the operational processes of five different cement production technologies—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies comprising a total of nine factories. The study evaluates their efficiency between 2017 and 2020 using network data envelopment analysis under non-homogeneous conditions across three modeling stages. An important aspect of this study is its focus on the entire supply chain, from raw materials to the final product. Although the raw materials employed vary among different cement production technologies, the end product remains largely consistent.IntroductionIn certain real-world scenarios, even with similar production technologies, the assumption of homogeneous decision-making units may not hold true. Practical applications often involve supply chain structures that differ significantly from others. For instance, some supply chains may, at certain stages, eject intermediate products to meet specific needs, a phenomenon not universal to all supply chains, resulting in non-homogeneous chains. The cement industry, including Iran, constitutes one of the pivotal economic sectors. Therefore, mitigating shortcomings, including resource and material waste reduction, can have a substantial impact on this industry and consequently on the broader economy. Due to varying climatic conditions, cement production employs diverse technologies, primarily categorized as dry or wet processes. This study investigates the operational processes of five different cement production methods—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies with a total of nine factories. Their performance between 2017 and 2020 is evaluated using network DEA under non-homogeneous conditions, encompassing three modeling stages.Materials and MethodsIn novel approaches, DEA is utilized to assess the performance of network decision-making units. The models typically assume homogeneity among decision-making units, which may not always align with real-world conditions. Practical situations often violate assumptions of unit homogeneity and uniformity in input and output parameters. Consequently, it is imperative to present and employ methods and models capable of accommodating non-homogeneous units. This study employs a scientific library research approach and practical purposive data collection to gather relevant information. This information informs specific adjustments to operational processes. Consequently, the development of a robust system for evaluating supply chain performance becomes essential. The study utilizes common models to evaluate efficiency under non-homogeneous conditions. Classification of operational processes and related data, followed by modeling using Lingo software, is employed in this research.Discussion and Result:This article consists of two parts. Initially, it introduces the fundamental performance evaluation model and subsequently delves into the three-stage model of data envelopment analysis (DEA) within the supply chain context. In the second part, the production processes of Portland cement are examined, covering dry, semi-dry, humid, semi-humid, and wet slurry processes. The proposed approach assesses the performance of four cement production companies over a four-year period. Efficiency calculations for nine factories are conducted in three stages:The first stage consists of three steps as follows:First step: Input and output parameters used across the entire production process are categorized based on the different production methods.Second step: Processes utilizing similar production steps, as determined in the first stage, are grouped into four categories.Third step: Efficiency assessments for factories sharing similar production stages from the previous step are conducted, resulting in the identification of nine categories.Second stage: The efficiency of each category, characterized by a common feature from the previous step, is calculated.Third stage: To determine the overall efficiency of each factory, the efficiencies of individual processes are multiplied.ConclusionsThe results indicate that the fourth cement production company exhibits the highest efficiency, while the first company has the lowest efficiency. Notably, the lowest efficiency for the years 2017 to 2020 was recorded by the first company in 2020, while the fourth company achieved the highest efficiency in the same year. Among the factories, the lowest efficiency was observed in 2017 for the first company's five semi-dry factories, the fourth company's four semi-humid factories in 2018, the fourth company's nine wet slurry factories in 2018, the third company's seven semi-humid factories in 2020, and the fourth company's four semi-humid factories in 2020, which recorded the highest efficiency. Further examination and identification of suitable solutions to enhance efficiency in cases with lower efficiency levels can follow this study.
supply chain management
fateme khanzadi; Reza Radfar; nazanini pilevari salmasi
Abstract
Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the ...
Read More
Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the chain. Adding effectiveness indicators along with LARG indicators and using the basics of the dynamic system to improve the efficiency of the supply chain is one of the innovations of this study. At first, by using research literature and studies, 12 headings of indicators were selected as LARG-E indicators. Then, with the Fuzzy Delphi method, the relationships and importance of each of these components were determined, and more important variables were modeled for further investigation. With using the concepts of dynamic systems, causal loops were drawn. Then, to check the function of the model, dynamic hypotheses were developed with the opinion of experts. In the next step, the flow diagram of the model and also the validation tests of the proposed model were done. Finally, by examining the outputs obtained from the proposed scenarios, it was found that most of variables have better behavior in LARG-E approach.IntroductionIn recent years, with the addition of various competitions in the world markets, many researches have been conducted to use new technologies and researches in order to improve the production process and increase the effectiveness of these competitions as much as possible (Mohghar et al., 2017). All the goals that work in this field increase the competitiveness of the organization. This competition is by reducing costs, being present in the market and satisfying the customer. To increase profits, protect the environment, keep the markets stable and meet the expectations of customers, organizations should be provided using the existing environments in a set of customers (Pisha et al., 2016). Use chain management requires the use of new facilities and improvements to previous findings such as lean, agile, resilience and green to increase speed and competitiveness, selection and decision-making to achieve the organization and maximum effectiveness.Today, supply chain specialists are looking for the integrated development of the supply chain model to increase the effectiveness and efficiency of the supply chain in order to increase competitiveness and reduce supply chain problems. In this case, there is a consensus among experts that there is no comprehensive model. All the mentioned cases make it inevitable to design a comprehensive and effective model for the supply chain. The verifiable issue is the conflicts and the non-alignment of all the indicators of the paradigms with each other. LARG paradigms, without considering the spirit of effectiveness in each supply chain, cannot fully protect it against continuous changes in the competitive market arena. A comprehensive model that pays particular attention to effectiveness while implementing LARG paradigms has not been examined in the literature review and the consensus of experts. Therefore, in this research, we are looking to design a comprehensive model in a LARG-effective manner so that the effect of various LARG-effective indicators on the performance of the supply chain can be investigated. The integration of LARG paradigms has been studied a lot so far, but its development is based on the concepts of innovation effectiveness of this research, and in this way, the dynamic system approach was used.Materials and MethodsTo formulate a LARG supply chain, first the framework, indicators and variables of each LARG paradigm were extracted from the research literature, then in order to develop them with effective concepts, the effective supply chain was studied. In order to implement the fuzzy Delphi approach, based on the effectiveness indicators extracted from the subject literature and LARG supply chain approaches, operational indicators were provided to the experts participating in the research in the form of a questionnaire via email and after initial coordination. After collecting the completed questionnaires, fuzzification operations, fuzzy averaging and then de-fuzzification were performed. The results were brought to the attention of the participants and they were asked to apply their desired changes according to the obtained results. This approach reached the saturation stage in the third round and there was no change in the opinions of the participants and the consensus of the panel experts was the final and trusted output of the Delphi method. Finally, according to these weights, 9 quantitative variables had the highest importance and were used for dynamic modeling. The simulation stage is done with the help of software and Nasim. According to the features of modeling based on system dynamics, this approach was chosen as the main research tool in this study because there are linear relationships between the variables and there are nested feedbacks between the variables of the subsystems, the importance of simultaneously improving the performance in different layers of the producer, supplier and distributor. Which is one of the goals of this research, with this approach, it can be a very suitable tool for decision-making by the senior managers of the organization.Discussion and ResultsOrganizations are trying to improve their competitiveness by adopting Lean, Resilient, Green and Agile strategies; But as it was said, the implementation of these paradigms, which sometimes have conflicting results, requires a new integration and index to align the goals. So far, many researches have been done by merging two or more paradigms, the combination of all 4 paradigms called LARG has greatly helped to improve the performance of supply chains, but in this research, in order to improve the conflicts between paradigms, a new concept of spiritual effectiveness was given to the supply chain. Understanding the dynamics of applying the above four strategies and their effectiveness was done using the dynamic systems approach. In this research, the indicators of the LARG supply chain were defined based on theoretical foundations and interviews with experts; then the effectiveness indicators were placed next to them. These indicators were implemented in the printing and ink industry. In this way, an effective LARG integrated system was defined; then, using a dynamic model, dynamic hypotheses were first defined and state and flow diagrams were drawn. After correctness of the model and validation of the model, two scenarios were examined for 8 important variables. After applying the scenarios, the performance of LARG and effective LARG was compared. By applying each scenario in the designed model, it was possible to check the effect of new indicators on the variables and their behavior.ConclusionsAs a result, if the components of the effective supply chain are properly integrated with the LARG concepts, they integrate the conflict that may exist between the LARG paradigms and play the role of synchronization and improvement as a ruler and standard. The effective management of the LARG supply chain may not be defined as an independent variable, but it is a result of variables and indicators that improved performance in most cases.
supply chain management
Ali Mahmoodirad; Ali Tahmasebi Notareki; Sadegh Niroomand
Abstract
The closed-loop supply chain is used in practice for several reasons. Firstly, returning products to the production cycle is important for its operation. Secondly, sustainability in the supply chain is a topic of interest for researchers, as the environmental impacts of industries are significant. In ...
Read More
The closed-loop supply chain is used in practice for several reasons. Firstly, returning products to the production cycle is important for its operation. Secondly, sustainability in the supply chain is a topic of interest for researchers, as the environmental impacts of industries are significant. In this paper, a multi-objective integer fuzzy mathematical programming model is presented to design a sustainable closed-loop supply chain under uncertain conditions. The proposed model aims to maximize profit and social impacts, while minimizing gas emissions into the environment. Since decision makers face uncertainty and doubt, trapezoidal intuitionistic fuzzy numbers are employed to determine the parameter values in the model. To convert the objective functions and model constraints into crisp forms, the expected value and the intuitionistic credibility measure are developed for the objectives and constraints, respectively. Finally, an interactive fuzzy programming approach is utilized to solve the crisp multi-objective problem. Three numerical examples are designed and solved to validate the model and assess the efficiency of the proposed solution method.IntroductionSupply chain management encompasses techniques aimed at coordinating all aspects of the supply chain, from raw material procurement to product delivery or recovery, with the objective of minimizing total costs while addressing conflicts among chain partners. Once raw materials have traversed the forward chain and been transformed into products or services, they may require repair, transformation, or proper disposal, which occurs within the reverse chain. The integration of forward and reverse supply chain methods gives rise to a closed-loop supply chain.Today, one of the primary concerns for organizational managers in supply chain network design is the presence of uncertainties, such as disruptions and uncertain input parameters. Uncertainties can have adverse effects on supply chain performance and decision-making at various network levels, including tactical, strategic, and operational decisions. As probabilistic planning necessitates historical data, which may not always be available or accurate, the theory of fuzzy sets can serve as a suitable option for expressing ambiguity and lack of certainty in parameters. In recent years, environmental factors have received increasing attention. There has been a growing recognition of the importance of environmental effects and the need to incorporate these effects alongside traditional indicators in supply chain design. Environmental considerations are crucial not only for compliance with government regulations but also for improving the organization's social standing from the customers' perspective. Moreover, with the rise of global warming and the accumulation of waste (both renewable and non-renewable, as well as electronic waste and ozone-depleting gases), the importance of managing and controlling these factors has become even more prominent. Despite the significance of environmental issues, there remains a noticeable gap in the supply chain literature concerning the provision of mathematical models based on real-world conditions and efficient solution methods for this problem. This paper focuses on the design of a sustainable closed-loop logistics network that aims to maximize profitability and social factors while minimizing environmental factors. The proposed integrated network considers multi-product and multi-state customer demand under conditions of uncertainty. The significance of this research lies in simultaneously addressing economic, environmental, and social considerations in the modeling process, as previous studies have mostly focused on single or dual objectives. Another innovative aspect of this article is the consideration of parameters in the form of intuitive fuzzy numbers for the design of a sustainable supply chain network.Materials and MethodsIn this research, a comprehensive model addressing the problem of sustainable closed-loop supply chain under intuitionistic fuzzy uncertainty is selected through library studies and internet research. Subsequently, the model is transformed into a deterministic multi-objective model utilizing the intuitionistic credibility measure. Recognizing that decision makers face not only uncertainty but also doubts, trapezoidal intuitionistic fuzzy numbers are employed to determine parameter values within the proposed model. To convert the objective functions and model constraints into their crisp equivalents, the expected value and intuitionistic credibility measure are respectively developed for the objective functions and constraints.FindingsBased on the selected confidence levels and numerical examples, the following observations can be made: In numerical example 1, the first objective function demonstrated that the ABS, SO, and TH methods performed best, respectively. However, in the second objective function, the order shifted to SO, ABS, and TH. Interestingly, all three methods performed equally in the third objective function. The performance of the solution methods in numerical example 2 mirrored that of numerical example 1. Moving on to numerical example 3, the first objective function indicated that the SO, TH, and ABS methods were the most effective, respectively. The order remained similar in the second objective function, and once again, all three methods performed equally in the third objective function. These results indicate the relative superiority of the SO solution method compared to the other methods employed. Additionally, concerning the execution time of the solution methods, numerical examples 1 and 2 exhibited nearly equal execution times for the methods. However, in numerical example 3, the SO, TH, and ABS methods displayed the best performance in terms of execution time, respectively. These findings further emphasize the relative superiority of the SO solution method compared to the others in terms of execution time. It is worth noting that the execution time of each method alone increases significantly with the problem's dimensions across all numerical examples.ConclusionsThis paper presents a multi-objective fuzzy optimization model for the design problem of a sustainable closed-loop supply chain. The model takes into account the concept of sustainability and aims to maximize the income and minimize the costs of the entire supply chain, while also minimizing environmental effects and maximizing social effects. The parameters are considered uncertain and are represented by intuitionistic trapezoidal fuzzy numbers. To handle this uncertainty, the model is transformed into a deterministic multi-objective optimization model using the expected value definition and a chance constraint based on the size of intuitionistic. The obtained deterministic multi-objective model is then solved using the interactive fuzzy mathematical programming method.
supply chain management
Mehdi Seifbarghy; Nastaran Bakhshizadeh
Abstract
Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other ...
Read More
Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other criteria except for price, like the production process, the features of parts and reliability of supply have long term effects on the performance of supply chains. In this research a general closed loop supply chain network including production centres, disassembly, refurbishing, and disposal sites is considered. An integrated two-phase model is given so that in the first phase, the proposed fuzzy-MOORA-reference point method is applied to suppliers’ assessment and the results from this phase is used in the second phase. In the second phase, a three-objective mixed integer linear programming model is proposed in order to determine the eligible suppliers, the locations of refurbishing sites and the material flows between the supply chain members. The objective functions are maximizing profit, suppliers’ evaluation and resiliency scores. Unsatisfied demand of customers is lost. The numerical results show the validity of the model and the role of stockout option in reaching better solutions based on the LP-Metric method.
supply chain management
Shaghayegh Vaziri; Farhad Etebari; Behnam Vahdani
Abstract
In this paper, we study a novel pickup and delivery problem called carrier collaboration (CC). This problem includes a set of heterogenous (refrigerated and general type) vehicles with specific capacities for serving perishable products to several pickup and delivery nodes. Each carrier can have reserved ...
Read More
In this paper, we study a novel pickup and delivery problem called carrier collaboration (CC). This problem includes a set of heterogenous (refrigerated and general type) vehicles with specific capacities for serving perishable products to several pickup and delivery nodes. Each carrier can have reserved and selective requests which can be delivered before the products are corrupted. The fleet of vehicles must serve reserved requests, but the selective requests can be served or not. Products are corrupted at a constant rate and a rate of corrosion in general type vehicles is greater than referigrated type veicles and the cost of using general one is less than referegireted. For the mentioned features, we develop a nonlinear mathematical model. The purpose is to find routes to maximize profits and reduce costs while at the same time, enhance customer satisfaction which is dependent on the freshness of delivered products. A Gnetic Algorithm (GA) is proposed to solve this problem due to its NP-hard nature. In this study, Variable Neighborhood Search (VNS) method is developed for improving the quality of initial solutions. Several instances are generated at different scales to evaluate the algorithm performance by comparing the results of an exact optimal solution wih that of the proposed algorithm. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time.
supply chain management
Mohammad ali Enayati shiraz; Seyed Abdollah Heydariyeh; Mohammad Ali Afshar kazemi
Abstract
Supply chain management can lead to a sustainable competitive advantage. The present study is in search of paper industry supply chain strategies with respect to supply chain dynamics and lean supply chain using dynamics in order to gain a competitive advantage in Iran Wood and Paper Industries Company ...
Read More
Supply chain management can lead to a sustainable competitive advantage. The present study is in search of paper industry supply chain strategies with respect to supply chain dynamics and lean supply chain using dynamics in order to gain a competitive advantage in Iran Wood and Paper Industries Company (Chooka). For this purpose, first, using organizational data and decision makers' participation, the system dynamics model was designed and after validation, the model was simulated in a ten-year horizon. According to the behavior of target variables and model sensitivity analysis in the simulation horizon, policies in line with lean supply chain strategy and sustainable profitability strategy of Chooka business were designed and applied separately and in combination to the model. And analyzed. According to the findings of the model simulation, productivity promotion policies through the use of lean methods in internal processes, increasing the quality of paper products, increasing innovation in the production and supply of paper products, improving raw material supply management And strategic partnership with suppliers of raw materials, industrial waste management, waste and solid waste management and staff empowerment have been presented as the best combined policies of the supply chain strategy of Iran's wood and paper industries.
supply chain management
Maedeh Fasihi; Seyed Esmaeil Najafi; Reza Tavakkoli-Moghaddam; Mostafa Hahiaghaei-Keshteli
Abstract
The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development ...
Read More
The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development of aquaculture and recycling of returned goods in reverse logistics would significantly help with preserving water resources, as well as sustainable development. Therefore, government agencies and aquaculture industry beneficiaries are interested in reverse logistics. This study is focused on the optimization of a closed-loop supply chain of fish. To this end, a new bi-objective mathematical model is proposed that both minimizes total costs and maximizes fulfilling customers demand in uncertainty situation. Several well-known multi-objective meta-heuristic algorithms and a proposed hybrid meta-heuristic algorithm are applied to identify Pareto solutions. The solutions are then compared in terms of performance metrics. Also, the epsilon-constraint method and sensitivity analysis are used to validate the algorithms and evaluate the performance of the model. Lastly, the VIKOR method is used to select the superior method. To demonstrate the capability of the proposed model, a closed-loop supply chain of trout in northern Iran is investigated as a case study. The results show that the developed model could be effective in reducing the costs and increasing customer satisfaction.
supply chain management
mohammadreza monjazeb; Mohammadkazem Sayadi; Mohammadjavad Farsayad
Abstract
Nowadays with increasing environmental pollution government's attention to the concept of the green supply chain has increased. The green supply chain produces a green product that is highly environmentally friendly. The purpose is to examine the impact of government intervention on competition between ...
Read More
Nowadays with increasing environmental pollution government's attention to the concept of the green supply chain has increased. The green supply chain produces a green product that is highly environmentally friendly. The purpose is to examine the impact of government intervention on competition between chains, the environment and social welfare. This article presents three different models. In the first model the two green and non-green supply chains are competing with each other and the government is not present. In the second model, the government creates a culture to use the green supply chain and in the third model, is taxing the non-green supply chain. The objective of government is social welfare. In both models of government intervention, the game is in the form of a Stackelberg. Backward analysis method is used to solve the model. This method is a backward inference process in problems with limited steps, with the aim of obtaining optimal action in each step. MATLAB and Maple software are used for mathematical calculations and obtaining decision variables. The results show that if the government intervenes in a cultural way, environmental damage will decrease. Another result is that the conditions for increasing social welfare in the state of culture are determined. It is also possible for the green supply chain to increase its price if certain relationships are established between the parameters. In the tax collection model, if the government aims to maximize social welfare, social welfare will increase under any circumstances compared to the absence of the government.
supply chain management
Akbar Rahimi; Alireza Boshehri; Arash Jafarian
Abstract
The oppressive sanctions of the superpowers in the supply of our country's military equipment, as well as the use of a significant number of helicopters with military and civilian applications (including transportation, rescue, agriculture, fire, crisis management, etc.), in the country, The importance ...
Read More
The oppressive sanctions of the superpowers in the supply of our country's military equipment, as well as the use of a significant number of helicopters with military and civilian applications (including transportation, rescue, agriculture, fire, crisis management, etc.), in the country, The importance of Iran Helicopter Support and Renovation Company (Panha) has doubled and the functional diversity of these helicopters has made it necessary for the company to move towards design and construction. Given the company's mission and existing constraints, including sanctions, effective supply chain management is a key factor in its success. Disruptions as a result of unexpected events are an integral part of the company's supply chain, and applying the supply chain resilience approach to deal with these unexpected events, rapid recovery and return to normal (before the event), as the only A company providing support and modernization services for helicopters in Iran is essential.The purpose of this research is to develop a supply chain resilience model for Panha Company. First, the supply chain resilience practices are identified, then, according to the necessity of the applicability of the final model, practices is categorized in the form of a two-dimensional matrix of importance - feasibility. Also, using fuzzy Delphi method, the most important practices and performance measures related to Penha Company were extracted. Finally, using interpretive structural modeling, a model is presented that shows the relationships between important and feasible practices of the company's supply chain resilience.
supply chain management
Abolfazl Kazai; amir mohammad khani; soraya birami
Abstract
As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research ...
Read More
As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research gap, this paper examines how SCQM capabilities and SCQM performance can influence firm innovation and operational performance, and how they interact with each other. For this purpose, the information of managers and experts active in the food industry in Golestan province was collected and analyzed through a questionnaire. Research findings show that SCQM practices have a positive effect on SCQM capabilities. Another result is that SCQM methods do not have a positive effect on the operational performance of food industries in Golestan province. This finding is significantly different from some previous studies. We also found that SCQM capabilities do not have a positive effect on innovation performance.
supply chain management
R. Ghasemy Yaghin; Fateme Darvishi
Abstract
This paper presents a global supplier selection model for the textile and clothing industry using a fuzzy multi-criteria group decision making approach. Then, the order quantity of each supplier is determined by a mathematical programming model. In the first step, a group fuzzy analysis hierarchical ...
Read More
This paper presents a global supplier selection model for the textile and clothing industry using a fuzzy multi-criteria group decision making approach. Then, the order quantity of each supplier is determined by a mathematical programming model. In the first step, a group fuzzy analysis hierarchical process approach is used to obtain the overall weight of the criteria and sub-criteria and then modified VIKOR is developed in order to calculate the vendor rating. In doing so, a modified VIKOR method with fuzzy-random data is extended due to the existence of both qualitative and quantitative criteria. The qualitative criteria are considered by fuzzy linguistic modeling and quantitative criteria from random data are formulated in a stochastic environment (based on historical data of suppliers). In the second step, a nonlinear programming model is developed to to determine the purchasing quantities from suppliers with multi-sourcing strategy. Finally, using a numerical study, the deployment of the above model is done in the clothing industry and crucial parameters are discovered by sensitivity analysis. Our findings indicate the critical role of customer’s demand and assigned capacity of suppliers in procurement plan.
supply chain management
Mostafa Ziyaei Hajipirlu; Houshang Taghizadeh; Mortaza Honarmand Azimi
Abstract
The purpose of this study is to design supply chains' upstream structure evaluation model in the automotive industry with spectral clustering based on the theory of complex adaptive systems. In this research, a method for evaluating the intersectionalities related to the structural complexity (horizontal, ...
Read More
The purpose of this study is to design supply chains' upstream structure evaluation model in the automotive industry with spectral clustering based on the theory of complex adaptive systems. In this research, a method for evaluating the intersectionalities related to the structural complexity (horizontal, vertical, and spatial) of supply chains by considering the functional characteristics of its components based on the resilience paradigm is presented. In this regard, a set of algebraic calculations and computational algorithms have been adapted to evaluate the structural design from the perspective of complex components. In the structural design evaluation model through spectral clustering, it is possible to enter information about supply chains in terms of interactions between components in the form of a network as a comprehensive model called similarity graph. According to the field findings, supply chain characteristics in terms of complexity can have interaction with component processing performance. This means that according to the concept of entanglement, the lack of a favorable environmental structure in supply chains can also negatively affect the resilience performance of its components. Findings from the perspective of achieving a supply chain evaluation model as an integrated whole have provided a suitable practical tool for evaluation and pathology of supply chains from the perspective of risk management.
