Mehdi Seifbarghy; Shima Zangeneh
Abstract
In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. ...
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In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. In this paper, a mixed integer programing (MIP) model presented in order to determine how to serve the customers at the time of disruption in distribution centers in a two-echelon supply chain, including distribution centers and customers. This model selects potential places that minimize traditionally supply chain costs and also the transportation cost after distribution centers disruptions. In fact, the model tries to choose the distribution centers facilities with lowest cost and highest reliability and also allocate them to customers. The problem divided into two sub-problems using Lagrangian relaxation approach. By examining sub-problems optimal conditions, a heuristic solution is used for the first sub-problem and a genetic algorithm is used for the second sub-problem to solve large-scale problems. Finally, numerical examples are presented to examine the performance and efficiency of the proposed model and approach
Maghsoud Amiri; Mahdi Keshavarz Gharabaei
Volume 13, Issue 36 , April 2015, , Pages 143-171
Abstract
Actual scheduling problems may necessitate the decision maker to consider a variety of criteria prior to make any decision. This research considers a single machine scheduling problem, with the objective of minimizing a combination of total tardiness and waiting time variance criteria in which the idle ...
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Actual scheduling problems may necessitate the decision maker to consider a variety of criteria prior to make any decision. This research considers a single machine scheduling problem, with the objective of minimizing a combination of total tardiness and waiting time variance criteria in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most important performance criteria in practical systems to avoid penalty costs of tardiness and waiting time variance is an important criterion in establishing Quality of Service (QoS) in many systems. Each of these criteria is known to be NP-hard and therefore the linear combination of them will be NP-hard as well. For this problem, we developed a genetic algorithm by utilizing its general structure. Two types of heuristic and random initial population and two distinct fitness functions are applied to genetic algorithms. The GA is shown experimentally to perform well by testing on various instances.
Maghsoud Amiri
Volume 6, Issue 15 , March 2007, , Pages 143-165
Abstract
After introducing Markowitz mean-variance model, decision makers (DMs) and financial planners paid much attention to the matter of portfolio selection, so that DMs explain purposes and investment requirements in the frame of multi-objective mathematic models which are more consistent with decision making ...
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After introducing Markowitz mean-variance model, decision makers (DMs) and financial planners paid much attention to the matter of portfolio selection, so that DMs explain purposes and investment requirements in the frame of multi-objective mathematic models which are more consistent with decision making realities in optimal portfolio selection. At now there are various methods introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. In this paper, considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective portfolio selection problem. In order to examine NCP performance and operational capability, we implemented a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.
Mohammad Hoseyn Karimi; Nima Esfandiari; Mahmoud Moradi
Volume 13, Issue 39 , January 2016, , Pages 145-170
Abstract
Many companies are pursuing agile manufacturing in order to reduce costs, improve customer service and attaining competitive advantage. After reviewing theoretical background and literature on agility, this paper presents agility attributes, criteria and enablers. Then a framework developed in order ...
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Many companies are pursuing agile manufacturing in order to reduce costs, improve customer service and attaining competitive advantage. After reviewing theoretical background and literature on agility, this paper presents agility attributes, criteria and enablers. Then a framework developed in order to prioritize and analyze agility indices with considering major competitive advantage. Hybrid Fuzzy Quality Function Deployment (FQFD) and Gap Analysis (GA) approach used to prioritize indices based on experts in an organization. Findings point out that “manufacturing management agility” has lowest maturity among agility enablers that lead this enabler to takes maximum importance. Furthermore, “manufacturing management agility” obtained most weight by FQFD, meaning this enabler has maximum priority and importance for organization. Interestingly, “knowledge management criterion” got first priority among all criteria by regarding maximum gap in gap analysis approach
Hiwa Farughi; Seiran Alaniazar; Seyedhamed Mousavipour; Vahed Moradi
Abstract
Nowadays, most of developed and developing countries, because of both limited resources and growing competitive markets, looking for to diagnose the causes of projects delay and are trying to develop solutions for decreasing amount of delay in next projects. In this paper initially notions related to ...
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Nowadays, most of developed and developing countries, because of both limited resources and growing competitive markets, looking for to diagnose the causes of projects delay and are trying to develop solutions for decreasing amount of delay in next projects. In this paper initially notions related to delay, project risk management, Failure Mode Effects and Analysis (FMEA) method have been reviewed and also construction projects of Kurdistan state organization of schools renovation have been examined. Then a framework based on Fuzzy FMEA and AHP model have been proposed in order to recognize the most important risks and determining the amount of effects of these risks on main objective of projects (i.e. time, cost and quality) and estimating their occurrence probabilities. Meanwhile along with calculating importance coefficient of factors, some ideas to prevent or decrease consequences of these factors have been recommended
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, ...
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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.
Hamid Shahbandarzadeh; Mohammad Hossein Kabgani
Abstract
This paper focused on locating ATMs problem. At first, this paper aims to identify effective factors in selecting ATMs appropriate locations. After selecting potential locations, optimal locations are determined through mathematical modeling. In this paper, effective factors to determine potential locations ...
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This paper focused on locating ATMs problem. At first, this paper aims to identify effective factors in selecting ATMs appropriate locations. After selecting potential locations, optimal locations are determined through mathematical modeling. In this paper, effective factors to determine potential locations are weighted through Fuzzy AHP. Finally, linear allocation technique with multi-objective approach is used to determine ATMs locations at Bushehr city. After literature review, 46 effective factors are identified and then, based on experts' opinion are categorized in 6 groups of demographic, economic - social factors, competitive – commercial factors, public utility (infrastructure and proximity) factors, investment factors and political - legal factors. Results from Fuzzy AHP show that demographic factors are the most important factors among others. Final results show that each of these six categories, can have different effects on decision makers.
mm uuu
Abstract
Mobile phone towers strength and coverage after happening natural disaster are one of the most important issues in set covering. Every day advances and developments of mobile phone technology have made the telecommunication industry and transferring equipment more important and subscribers and users ...
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Mobile phone towers strength and coverage after happening natural disaster are one of the most important issues in set covering. Every day advances and developments of mobile phone technology have made the telecommunication industry and transferring equipment more important and subscribers and users of the mobile phones and increasing which requires better planning. So, the subject of coverage ability of the cell phone towers is very important. Natural disasters for example earthquake, flood, storm, landslides and activating volcano affect roads, bridges, communication systems, electrical supplying and availability to facilities. Extensive human casualties and huge economic damages are showing prediction necessity and programming for facing these events preventing crisis occurring This paper develops location and strengthening of cell phone towers to maximize service coverage and minimize the loss of communication if natural disaster happens. In addition, proposed model considers backup and emergency coverage. We present a case study of our approach for disaster planning for disaster scenario in a region of Iran. Numerical experiments demonstrate the significance and applicability of the developed model for actual decision-making problem.
Reza Yousefi Zenouz; Akbar Hassanpoor; Parisa Mousavi
Volume 13, Issue 37 , July 2015, , Pages 161-185
Abstract
Risk is inherent and inseparable part of life and business. Always uncertainty condition arising from incomplete information and data or ungovernable variables, associated with opportunities and threats.Nowadays many organizations and companies have relied heavily on information systems and information ...
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Risk is inherent and inseparable part of life and business. Always uncertainty condition arising from incomplete information and data or ungovernable variables, associated with opportunities and threats.Nowadays many organizations and companies have relied heavily on information systems and information security management has transformed to an important organizational topics. And due to the fact that the use of information systems security may be created some risks, an effective risk management process, will result in a successful security program. Risk management includes risk identification process, risk assessment and risk-reduction efforts to acceptable levels. The objective of this research is to prioritize information security risks, in order to provide a mechanism to enhance the security of enterprise information. To this end, a model has been presented for organizational information security risk assessment using the fuzzy AHP and Bayesian networks. In the assessment process, risks impact by fuzzy AHP and risks probability by Bayesian networks have calculated and finally The risks Prioritized. The findings suggest In the case study, the risk of lack of knowledge and lack of proper training in the field of information security, have the highest priority and attention is needed most
amir daneshvar; Mahdi Homayounfar; elham akhavan
Abstract
Data classification is one of the main issues in management science which took into account from different approaches. Artificial intelligence methods are among the most important classification methods, most of them consider total accuracy function in performance evaluation. Since in imbalanced data ...
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Data classification is one of the main issues in management science which took into account from different approaches. Artificial intelligence methods are among the most important classification methods, most of them consider total accuracy function in performance evaluation. Since in imbalanced data sets this function considers the cost of prediction errors as a fix amount, in this research a sensitivity function in used in addition to the accuracy function in order to increase the accuracy in all of the predefined classes. In addition, due to complexity in process of seeking information from decision maker, NSGA II algorithm is used to extract the parameters (Weight vector and cut levels between classes). In each iteration, based on the estimated weight vector and data sets, the algorithm calculate the score of each alternative using Sum Product function and then allocates the alternative to one of the classes, comparing to the estimated cut levels,. Then, using the fitness functions, the estimation class and the actual class will compare by two algorithms and this process will continue since optimizing the parameters. Comparison of the NSGA II and NRGA algorithms show the high efficiency of the proposed algorithm.
Majid Esmaelian; Sayedeh Maryam Abdollahi
Abstract
Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific ...
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Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific periods throughout a week for a given semester while satisfying specific constraints. In this study, we present two novel binary integer linear programming models for the university timetabling problem. Using a GAMS IP Solver, several experiments through each model are solved and the results (the number of the decision variables and solution time) are compared and analyzed. The computational comparison indicates that the second model can be used for modeling large-scaled problems and has less computational and size complexity. Therefore, the second model is applied to optimal scheduling the courses planned for the faculty of administrative science and economics (ASE) at Isfahan University for one semester and the results consist of table of courses planned for teachers, students groups, rooms and workdays are presented
Seyyed Hossein Abtahi; Ahmad Hasani Kakhaki
Volume 4, Issue 12 , March 2006, , Pages 163-182
Abstract
Forecasting is a base of any planning method especially human resource planning. One of the most important problems of organizations is human resource and personnel's problems. Accompanied by advance in the human societies and therefore complication in organizations, these subjects create opportunities ...
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Forecasting is a base of any planning method especially human resource planning. One of the most important problems of organizations is human resource and personnel's problems. Accompanied by advance in the human societies and therefore complication in organizations, these subjects create opportunities and challenges for managers. A proper human resource planning can increase job satisfaction, promote quality and favorites of manpower and decrease staffing cost. Nowadays quantitative and qualities tools and methods are existent that utilize for human resource planning. This article is a research in tree dependent's firm of holding Software Company that applies one of most common method in planning. For estimate human resource needs in future stage, using tree previous year information that confine in six stages and duration of any stage is six month. Markov chain analyze is a method that use for estimate human resource in four job categories. Content scope in this research is human resource issues.
Ali Mohamadi; Payam Shojaei; Hamid Reza Yazdani; Mohammad Reza Sadeghi Moghaddam
Abstract
Regarding to the increasing importance of supply chain risk in the lastdecade in general and projects especially, in this research the dimensions andelements of supply chain risk of projects have been determined. Therefore,Fars Gas Transfer Pipeline projects were considered to discover codes andthemes ...
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Regarding to the increasing importance of supply chain risk in the lastdecade in general and projects especially, in this research the dimensions andelements of supply chain risk of projects have been determined. Therefore,Fars Gas Transfer Pipeline projects were considered to discover codes andthemes according to the phenomena by using Grounded Theory (Corbin andStrauss method). Based on final paradigm model, project supply chain riskmanagement issue was categorized in 6 main dimensions, 19 sub-dimensionsand 57 codes. The results show that supply chain risks as a core phenomenon,consists of environmental risks, organizational risks and network risks. Todo this, we use theoretical sampling and interview with 10 experts from Gasstate company and some suppliers. These interview was deep one becausewe employed open questionnaire. Then by using open encoding, axialencoding and selective encoding, paradigm model was extracted. The mainphenomenon placed the center of model and other themes joined to that
Akram Oveysiomran
Abstract
Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, inputs and outputs of reginal power companies are selected with artifitial neural network. The application of neural network in the selection of inputs and outputs of reginal power companies is not a precedent ...
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Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, inputs and outputs of reginal power companies are selected with artifitial neural network. The application of neural network in the selection of inputs and outputs of reginal power companies is not a precedent in the literature and it is considered the main advantage of the proposed method. In order to train two layers MLP neural network, after presenting of error resilience, learning method was used. After neural network training, neural network performance is examined by using the test set. RMSE value for 15 test set equals 0/0269 which reflects the high accuracy of training network. The Sensitivity Analysis of the studied parameters which are the same inputs and outputs of Data Envelopment Analysis, with ten percent increase of parameter, compared to the prior one was carried out and output relative error average for neural network parameters was calculated. Based on the output relative error average, inputs and outputs were determined. By comparing the efficiency scores of regional electricity companies before and after reducing the number of variables, it is noticed that the number of efficient companies during the above four periods decreased from 50 percent to 11 percent. Finally, the neural network application in inputs and outputs selection of the regional electricity companies was unprecedented in the literature and this is the main advantage of this method.
Somayeh Kavianpour; Gavad Rezaeian
Abstract
Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on ...
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Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on job satisfaction and quality of received services. A linear mathematical model is proposed and since this problem is NP-hard, Genetic Algorithm is provided for solving the problem and finally Implemented in Imam Khomeini hospital of Noor city as a real sample. Computational results and performance of the proposed algorithm in terms of solution quality and computational time were analyzed. Accreditation standards for hospitals as well as the Productivity laws are used in the proposed model. Production of timetables by the proposed model, resulting in improved satisfaction levels of nurses and their job performance.
Mohammad Ali Shariat; Soleiman Iranzadeh; Alireza Bafandeh Zendeh
Abstract
The speed of competitiveness and organizational innovation, specifically with respect to corporate sustainability improving functions and environmental stress on manufacturing companies in predicting economic, social, and ecological advantages of their processes and products, significantly increased ...
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The speed of competitiveness and organizational innovation, specifically with respect to corporate sustainability improving functions and environmental stress on manufacturing companies in predicting economic, social, and ecological advantages of their processes and products, significantly increased in the recent decade. This condition faced all manufacturing companies across the world with a new challenge, making them try not only to maintain their current competitive status by developing and implementing sustainable production tools, but also to follow a sustainable progress that considers social, economic, and environmental matters at the same time. This study focused on business sustainability with a new perspective in industrial symbiosis, and tried to develop a sustainable production model through identifying different dimensions of sustainable production from managerial viewpoints of successful manufacturing companies in Semnan Province, Iran. To this end, managers of 33 successful companies across the province with at least five-year continuous work experience were interviewed, using the repertory grid technique. As a result, 33 single individual repertory grids and 175 initial individual constructs of sustainable production were fabricated. Finally, the sustainable collective grid of sustainable production, including 87 secondary constructs within 11 sections were drawn and analyzed through cluster analysis in SPSS. At the end, a sustainable production model with 11 pivots and 87 constructs within 4 sections, along with four production strategies (economic production, lean production, green production, and sustainable production) were proposed
iman ghasemian sahebi; Hamidreza FAllah Lajimi; Alireza Arab
Abstract
Operational strategy is one of the essential tools for operations management in the current competitive environment. The operational strategy focuses on the activities of the operational levels in line with the competitive priorities of the organization. Hence, the present study tries to review and design ...
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Operational strategy is one of the essential tools for operations management in the current competitive environment. The operational strategy focuses on the activities of the operational levels in line with the competitive priorities of the organization. Hence, the present study tries to review and design the most appropriate operational strategies for increasing the efficiency of the Automotive manufacturing industry. However, given that the supply chain of this industry is dependent on the changing and unpredictable environment of the market and environment such as raw materials, suppliers' conditions, government policies and sanctions, and the price fluctuations caused by currency volatility, so the need for operational strategies is felt. Therefore, after determining the annual goals for each output, continuous flow production system was identified as the appropriate system for achieving the desired situation in the studied company. At last, adjustments were provided to improve the company's status in each of the production levers. Output Prioritization and development of the Miltenburg model with the Fuzzy Best-Worst Method took place for the first time According to the experts' opinion, which cost criterion identified as the most important output and the Quality criterion placed at the second level of important; and also Flexibility, performance and delivery criteria placed at the next level of important.
ali shariat nejad; Saba Asgari zahabi
Abstract
Today, with increasing environmental uncertainty, one of the ways to adapt to changes and ensure a permanent job is the tendency towards hybrid entrepreneurship. the present study aimed to survey the impact of hybrid entrepreneurship on career success with the mediating role of diverse career path orientation ...
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Today, with increasing environmental uncertainty, one of the ways to adapt to changes and ensure a permanent job is the tendency towards hybrid entrepreneurship. the present study aimed to survey the impact of hybrid entrepreneurship on career success with the mediating role of diverse career path orientation was conducted. This research is applied research and it is among the descriptive and survey researches. The statistical population of this study is the managers and employees of companies located in industrial states in Lorestan province. Using the Cochran sample calculation formula, the sample size of 350 people was determined and the sample members were selected using the available sampling method. Data collection tools in the present study were standard questionnaires whose validity and reliability were confirmed by content method and Cronbach's alpha and combined reliability. the structural equation modeling approach and PLS software have been used to test the hypotheses. The results of the hypothesis indicate that hybrid entrepreneurship has positive impact on diverse career path orientation and career path success. as a general result, it should be noted that due to the high rate of bankruptcy and loss of jobs, people who work in industrial estates and in professional jobs, can with a hybrid entrepreneurial strategy and direction orientation. A diverse career that leads them to new and entrepreneurial businesses, try your luck at the success of a new career and another business, and take advantage of the benefits of second job, unemployment and state of mind. Unemployment to be safe.
S.jamal’aldin Hosseini; Jalal Rezaeenour; mohammad masoumi; Amir Hosein Akbari
Abstract
One Knowledge Management (KM) as one of the Supply Chain performanceimprovement factors can be strengthened through frameworks like EFQM ExcellenceModel in order to achieve competitive advantage. First, the KM enablers in SC areclassified based on EFQM enabler criteria. Then, the importance of each KM ...
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One Knowledge Management (KM) as one of the Supply Chain performanceimprovement factors can be strengthened through frameworks like EFQM ExcellenceModel in order to achieve competitive advantage. First, the KM enablers in SC areclassified based on EFQM enabler criteria. Then, the importance of each KM enabler isevaluated by fuzzy DEMATEL-ANP. In addition, Analytical Hierarchy Process (AHP) isapplied to evaluate the importance of each KM enabler in knowledge sharing amongsupply chain people. In the research, the multi-objective mixed integer programming isused to optimize knowledge management and select KM strategy in each part of SC.Likewise, it is approved to select suitable members of SC for Research and Development(R&D) unit of SC. Results show that each part of SC should focus on developing someKM enablers, and selection of a suitable strategy. These results also emphasis theeffectiveness of each KM enabler and their development in selecting of suitable membersfor R&D unit of SC.
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 ...
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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.
Shima Salehi; Mohammad Taghi Taghavifard; Ghanbar Abbaspour esfeden; a alirezaee
Abstract
The integration of supply chain decisions aims to reduce costs and delivery time for customers. However, uncertainty in supply chain parameters, particularly demand, can disrupt this integration. The increased interest in probabilistic planning and simulation models in supply chain modeling is a response ...
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The integration of supply chain decisions aims to reduce costs and delivery time for customers. However, uncertainty in supply chain parameters, particularly demand, can disrupt this integration. The increased interest in probabilistic planning and simulation models in supply chain modeling is a response to this demand uncertainty. Therefore, the main objective of this study was to develop a multi-level, multi-product, multi-period supply chain network model that considers conflicting objectives such as cost minimization, delivery time minimization, and system-wide reliability maximization. The supply chain network under investigation consisted of four levels or subsystems: suppliers, manufacturers, distributors, and retailers. In this study, it was assumed that demand follows a random probabilistic distribution function. Consequently, simulation techniques were employed to estimate costs, including shipping costs, lost sales costs, and other expenses. After developing the multi-objective model, various scenarios were created based on different perspectives of inventory levels, namely minimum inventory, maximum inventory, and average inventory level. For each scenario, objective-related values were estimated. Ultimately, based on the Pareto optimal solutions obtained for each case of the model, the Vickor decision-making method was used to rank the answers and select the best solution from the proposed model. The results indicated that the second scenario, considering the average inventory level, was identified as the optimal solution for the described model.IntroductionToday, supply chain management (SCM) encompasses the entire production planning process for the supply chain, from raw material suppliers to the final customer. This has become a focal point for numerous researchers. In most supply chain designs, the objective has been to transfer products from one layer to another in order to meet strategic, tactical, and operational demands while minimizing complications arising from interrelationships and uncertainties across the chain. These challenges have posed significant decision-making hurdles in the supply chain domain. Supply chains can be regarded as complex systems wherein various factors interact with each other, resulting in emergent properties. Designing a versatile supply chain to address conflicting and diverse objectives requires considering them simultaneously and striking a balance among different criteria. The dynamic and intricate nature of the supply chain introduces a high level of uncertainty, thereby impacting the decision-making process in supply chain planning and influencing overall network performance. Based on the aforementioned issues, the focus of investigation includes the following: The examined supply chain network comprises four levels or subsystems, namely suppliers, manufacturers, distributors, and retailers. Raw materials are sourced from suppliers and sent to production factories, where each product is manufactured using a specific combination of raw materials. The products are then transported from manufacturers to distribution centers, and subsequently forwarded to retailers. The market is divided into different regions, and customer demands are fulfilled through visits to the retailers. Demand is assumed to be random and follows a probability distribution pattern. Consequently, simulation techniques are employed to estimate costs, including transportation costs, lost sales costs, and other expenses. Scenarios are created based on different perspectives at each level, focusing on inventory levels (minimum, maximum, and average). For each scenario, the values associated with the investigated objectives are estimated.Materials and methods In this research, data collection involved the examination of relevant literature, including articles published in international journals, books, and treatises. Documentary studies were conducted to gather information. To analyze the collected data, simulation and multi-objective programming concepts and methods were employed. Minitab and ED software were utilized for statistical analysis and simulation purposes.ConclusionsConsidering that the model can be solved under different conditions, including the current situation and various scenarios, the answers obtained for each state are Pareto optimal. This means that it is not possible to determine a single best answer for each state of the model. Therefore, before comparing the scenarios with each other, the Pareto optimal answers for each scenario should be ranked to identify the best options. In this research, a model for designing the supply chain network was presented, taking into account demand randomness. To better understand the proposed model and demonstrate its practicality, numerical examples were examined and evaluated using different scenarios and the Lingo software. It is important to note that the developed model in this study is independent of the number of facilities at each level of the supply chain and the parameter values. Therefore, the general form of this model can be applied to any production environment that aligns with the patterns presented in this research. The proposed model initially employed the design of experiments to estimate the mathematical relationship related to the cost objective function. After developing the multi-objective model, the Lingo software was used to solve the sample problem and evaluate the results under different scenarios. Finally, based on the Victor decision-making method, the Pareto optimal solutions for each state of the model were used to rank the answers and determine the best mode for the proposed models. Based on the obtained results, the third option or the second scenario is suggested as the preferred choice for the described model, considering the index values associated with each option
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 ...
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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
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 ...
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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.
vajhollah ghorbanizadeh; Mohammad Amini; Jafar Rashidi
Abstract
There is a serious competition between Allameh Tabataba'i, shahid Beheshti, and Tehran Universities to attract the best students. In other side, students have considered several indicators to choose university for higher education. The aim of this research is to determine management faculties’ ...
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There is a serious competition between Allameh Tabataba'i, shahid Beheshti, and Tehran Universities to attract the best students. In other side, students have considered several indicators to choose university for higher education. The aim of this research is to determine management faculties’ competitive position in these Universities and also to find an answer to this question: what is the position of Allameh Tabataba'i University postgraduate students compared to two other universities based on variables such as: rank of entrance examination, number of acceptance , average of undergraduate scores, type of undergraduate university, relationship between educational field in BS and MA, and students age. This practical research uses descriptive study and has comparative approach. The data was collected from three management faculty for 2009 to 2014. The findings indicate that Allameh Tabataba'i University has accepted MA students in management more than two other universities and its MA students have lower average of entrance examination rank. There were no main distances on average of undergraduate scores and MA students’ age between these universities. There were similar situations about the other variables
Ali Bonyadi Naieni; Sirous Amirghodsi; Ahmad Makui
Abstract
One of the important decisions in the supply chain is the supplier selection affecting different sectors and objectives of a chain significantly. In supplier selection area, product/technology selection, product/technology transfer method selection, and product/technology supplier selection are three ...
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One of the important decisions in the supply chain is the supplier selection affecting different sectors and objectives of a chain significantly. In supplier selection area, product/technology selection, product/technology transfer method selection, and product/technology supplier selection are three debatable factors. Hence, in this paper, criteria influencing these three indicators will be identified and their importance will be ranked by Gray-DEMETEL and Best-Worst Method (BWM). Then, the priority of the options will be determined using Gray Analytical Network Process (GANP), which is one of the strongest decision-making methods. This paper attempts to demonstrate the superiority of the BWM method in determining the importance of criteria while comparing previous methods in this group. The compliance rate obtained for the BWM confirms this claim. In order to investigate the proposed approach, a case was conducted with 5 final suppliers, 3 technologies and 5 technology transfer methods, which ended with the selection of the best supplier with the highest technology and capable of transferring the technology by the optimal transfer method.
