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, ...
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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.
Ali Akbar Mohamadian; Masoud Simkhah
Abstract
Supplier selection is one of the most important problems in the field of management and optimization. It aims to optimize the cost of supply, quality of products and services, and the risk of non-supply, among others. However, existing models often overlook the risk of non-supply and the brand effect ...
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Supplier selection is one of the most important problems in the field of management and optimization. It aims to optimize the cost of supply, quality of products and services, and the risk of non-supply, among others. However, existing models often overlook the risk of non-supply and the brand effect on demand. In this research, a supplier selection integer model is developed that considers lead time and the risk of non-supply. To solve this model, the LOKAD benchmark database is utilized, and a new adaptive variable neighborhood search algorithm is introduced, incorporating a scoring strategy to handle the model's complexity and obtain optimal or near-optimal solutions. The obtained Pareto solutions outperform traditional results, as confirmed by the Wilcoxon test. Sensitivity analysis of the solutions on the budget demonstrates that the final profit is more sensitive compared to lead time. Furthermore, distance from the ideal and diversity measures are used to quantitatively compare the results. IntroductionSupplier selection involves identifying, evaluating, and contracting with suppliers to meet an organization's requirements for raw materials and related infrastructure. It plays a crucial role in financial resource allocation and product/service quality. The main objectives of supplier selection include reducing purchasing risks, minimizing lead time, and enhancing quality. Many organizations face multiple criteria for selecting suppliers, such as receipt risk, green criteria, and lead time. Mathematical modeling and optimization techniques are commonly employed to achieve these objectives. However, existing models often lack real-case assumptions, motivating researchers to extend models in this environment. This research addresses these gaps by developing a mathematical model for supplier selection that considers the risk of non-supply and the substitution rate of inventory-less products. Materials and MethodsTechnically, the conducted modeling is a quantitative research in which data has been collected using library-based tools. Additionally, the statistical population corresponds to the LOKAD company, and a sample of its information is publicly available and will be utilized in the numerical computations phase of this research. This research develops a novel supplier selection multi-objective mathematical model that considers the risk of non-supply and substitution rate of demand when a product is inventory-less. Additionally, a modified adaptive variable neighborhood search (AVNS) algorithm is proposed to solve the model. While the focus of this paper is on the retail industry, the proposed model can be adapted to any industry. Discussion and ResultsThe developed model will be solved using data related to the LOKAD company, which was collected during a one-year period in 2018. This dataset includes sales and purchasing information of products related to the LOKAD company, encompassing details about the suppliers of the products and their brands. The utilization of this dataset is due to the fact that many articles have made use of it for its detailed information provided by the LOKAD company. In order to compare the method, the Wilcoxon test is used to compare two groups of variables, which can determine the presence of a difference between them. The observations reveal that the substitution rate of demand significantly affects the results and can alter the selection of final suppliers. Budget limitations are another important factor, where increasing the budget leads to higher profits by enabling the selection of more competent suppliers and high-quality products for customers. ConclusionsSupplier selection is a challenging problem in various industries. The experiments conducted in this research demonstrate that increasing the budget limitation results in higher profits, as customers prefer products or services with higher levels of quality. The developed mathematical multi-objective model incorporates real-case assumptions such as the risk of non-supply and substitution rate of demand. The model is solved using the proposed modified AVNS algorithm. The solutions obtained are analyzed using mean ideal distance and diversification metric measures to ensure their reliability. The analysis highlights the significance of budget limitations, which outweighs the impact of lead time in supplier selection problems. Ultimately, the model provides an optimal combination of suppliers. Additionally, the sensitivity analysis performed on the budget constraint reveals that changes in the budget have a greater impact on the final profit compared to lead time. The proposed model effectively determines the allocation of purchases from each supplier to enhance the final profit. In this regard, an initial estimation of future demand is considered as deterministic, although transforming this parameter into a probabilistic form can make the model more robust.
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.
Marzieh Karimi; Abolfazl Kazemi
Abstract
Supplier selection is the process by which firms identify, evaluate, and contract with suppliers. The supplier selection process deploys a tremendous amount of a firm's financial resources. Nowadays, supplying the required resource of organizations has become an important business approach so a competitive ...
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Supplier selection is the process by which firms identify, evaluate, and contract with suppliers. The supplier selection process deploys a tremendous amount of a firm's financial resources. Nowadays, supplying the required resource of organizations has become an important business approach so a competitive advantage may be gained by the selection of the best suppliers to provide products/services more effectively and efficiently. Many models have been developed for solving supplier selection problem. In this paper, in addition to considering the incremental discount strategies, cost of shortages is also considered so far has not been considered. In this model, two objective functions of cost minimization of the buyer, and maximize quality of product is considered. To solve the proposed supplier selection model, an improved harmony search algorithm is used. The results show that the proposed algorithm works properly in the term of both CPU time and the quality of solutions. Finally, some numerical examples for model analyses are presented.
Reza Esmaeilpour; Adel Azar; Mohammad ShahMohammadi
Abstract
Nowadays many organizations involved in environmental, social and economic concerns and measure supplier performance on the fields; including the effect that "corporate social responsibility" could have on the suppliers’ selection. The aim of this study is determine of a model to selection of suppliers ...
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Nowadays many organizations involved in environmental, social and economic concerns and measure supplier performance on the fields; including the effect that "corporate social responsibility" could have on the suppliers’ selection. The aim of this study is determine of a model to selection of suppliers based on corporate social responsibility. By a review of research literature and obtaining the opinion of experts, the issues were identified in the 5 dimensions (organizational commitment, employee, commitment to society and citizenship, moral commitments, environmental commitments) and 17 indicators. Then the matrix structured questionnaire was developed to determine the intermediate relationship of these indicators. Questionnaire's obtained data analyses using ISM so it was traced 6 levels in an interactive network that indicator "focus on sustainable development" was at the highest level. Also, influence and dependence of the indicators relative to each other on the matrix influence-dependence was evaluated. The most influential indicator in the matrix influence-dependence is "Providing relevant training in CSR to the suppliers”; so the implementation of Corporate Social Responsibility in the selection of suppliers depends on their training and to be with this attitude, long-term plans would be design on the basis of social responsibility training specifically for suppliers
Adel Azar; Mahdi Abedini Naeini; Amir Afsar; Mohammad Sabet Motlagh
Volume 14, Issue 42 , October 2016, , Pages 1-30
Abstract
Supplier selection and quota allocation is an important decision in supplychains. This decision can be considered as a complex multi-criteria groupdecision making problem. This decision in many practical situations is verydifficult for vague and uncertain environment. This vagueness and uncertaintycan ...
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Supplier selection and quota allocation is an important decision in supplychains. This decision can be considered as a complex multi-criteria groupdecision making problem. This decision in many practical situations is verydifficult for vague and uncertain environment. This vagueness and uncertaintycan be handled by using fuzzy set theory. Therefore, this paper proposed afuzzy MCDM model to evaluate candidate suppliers and quota allocation. Ahybrid ANP-VIKOR method in fuzzy environment applied first with 16criteria to evaluate suppliers. Then, a fuzzy multi-objective mathematicalmodel is used to quota allocation. Finally, the fuzzy model is solved by Tiwarimethod. An illustration with a data set from a realistic situation is presented todemonstrate the effectiveness of the proposed model.
Yalda Yahyazade; Laya Olfat; Maghsod Amiri
Abstract
Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, ...
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Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, price, flexibility and delivery times is very difficult and complex and requires accurate and appropriate tools. On the other hand today's competitive environment due to its variable nature, has added the uncertainty and ambiguity in decision-making. The problem of supplier selection is not an exception as well and it seems suitable to use the robust optimization methods in such circumstances. The mentioned method is used in this research with the goal of supplier selecting and determining the amount order of products considering all restrictions in order to minimize the costs and maximize the utility of purchase in the condition of uncertainty. In this paper, a multi-objective deterministic model is presented to solve the problem, and then the deterministic model is converted to the robust model using the scenario-based robust method and then is solved using the LP metric method so optimal amount of order is obtained from each of suppliers at any period. To determine the weight of each of suppliers, Analytical Hierarchy Process (AHP) is used as well.
Mojgan Khorasani; Abolfazl Kazemi
Abstract
This paper investigates a supplier evaluation and selection model which considers features of leagile supply chain and allocates orders to the selected suppliers. In the proposed model, potential suppliers are evaluated by applying a multi-objective model with respect to the key features of leagile supply ...
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This paper investigates a supplier evaluation and selection model which considers features of leagile supply chain and allocates orders to the selected suppliers. In the proposed model, potential suppliers are evaluated by applying a multi-objective model with respect to the key features of leagile supply chain, including the ability to respond to demands, reducing delay time and costs (which are the winning factors for being the winner of market in this supply chain), as well as considering the capacities and limitations of organizations and suppliers. The proposed model allows buyer to select several suppliers. In addition, the model is multi-products and multi-periods. Due to long time and inefficiency of exact methods for large-sized problems, in addition to Lingo software, Genetic Algorithm is used to achieve the optimum solution
Parham Azimi; Farzaneh Goldar; Esmaeil Mehdizadeh
Volume 13, Issue 36 , April 2015, , Pages 115-142
Abstract
Supply chain management (SCM) is one of the most important competitive strategies used by modern companies. The main goal of supply chain management is integration different suppliers to fulfill market demand. Therefore, evaluation and selection of suppliers has critical role and significant effect on ...
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Supply chain management (SCM) is one of the most important competitive strategies used by modern companies. The main goal of supply chain management is integration different suppliers to fulfill market demand. Therefore, evaluation and selection of suppliers has critical role and significant effect on supply chain management. This paper presents hybrid model based on clustering approach and suppliers' selection. At first, K-harmonic means clustering method which is one of the most popular methods in clustering analysis is used for clustering suppliers. Then, according to theoutput of clustering, a multi-objective model is considered to select the best supplier. Since the model belongs to the class of NP-hard optimization problems, two meta-heuristic algorithms named Non-dominated Sorting Genetic Algorithm (NSGAII) and Non-dominated Ranked Genetic Algorithm (NRGA) is used for solving model in reasonable time. Computational results show that the clustering analysis can be considered as an effective way to the suppliers' selection. Also, several data sets are applied to evaluate the effect of clustering analysis on suppliers' selection
Payam Chiniforoshan; Behrouz Pourghannad; Rouzbeh Azizmohammadi; Seyed Hossein Razavi
Volume 6, Issue 16 , June 2007, , Pages 55-74
Abstract
Now days one of the main strategies and policies of firms is purchasing parts from external suppliers. For decision making about selecting suppliers, are considered the different criteria. But because of changes of management levels and external suppliers strategies, could not determine input data precisely. ...
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Now days one of the main strategies and policies of firms is purchasing parts from external suppliers. For decision making about selecting suppliers, are considered the different criteria. But because of changes of management levels and external suppliers strategies, could not determine input data precisely. Hence, considering supplier selection problem with regard to the uncertain criteria is necessary. In this paper, a combinatorial model from the well-known method of Compromise Programming (CP) and Interval Programming will be proposed that is called Interval Compromise Programming (ICP). The model can be used for optimizing multi-objective interval problems. For illustrating the proposed model, will be presented a supplier selection problem by considering the objectives of minimizing rejects and purchase cost and maximizing quality of purchased products, where are considered the input parameters as interval numbers. The obtained results compared to the ideal value of each objective can present a representation from situation of optimistic and pessimistic of the problem under uncertainty.
