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 ...
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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
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.
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 ...
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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.
