A multi-objective optimization model of a closed-loop supply chain for supplier selection and order allocation under uncertainty: A case study of retail stores for protein products

The supply chain plays an essential role in the competition between companies. Supplier selection is of great importance considering the influence on the quality of the final product, the return rate, the price of the product, and the sustainability of the whole supply chain. Moreover, the real world is facing much uncertainty. In this uncertain environment, applying fuzzy decision support systems is promising. The main objective of this study is to develop an optimization model to choose suppliers and determine the number of orders for perishable protein products in uncertain conditions in a retail store. A fully fuzzy multi-objective model for a retailer company's closed-loop supply chain is developed to minimize costs and waste and maximize profit, customer satisfaction, quality, and margin under uncertainty. The proposed model is applied in a real case study of Iranian retail stores for protein products. The results proved the potential of the proposed model to improve the closed-loop supply chain's sustainability performance.

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Publication Details

Journal
Transportation research procedia
Published
2025-01-01
DOI
https://doi.org/10.1016/j.trpro.2024.12.046
Citations
5
Primary Topic
Optimization and Mathematical Programming
Type
article
Field-Weighted Citation Impact
6.07
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article

A multi-objective optimization model of a closed-loop supply chain for supplier selection and order allocation under uncertainty: A case study of retail stores for protein products

Samira Keivanpour, Hossein Safari, Mina Kazemi Miyangaskary
5 citations
Transportation research procedia
Optimization and Mathematical Programming
6.07
article

A multi-objective optimization model of a closed-loop supply chain for supplier selection and order allocation under uncertainty: A case study of retail stores for protein products

Samira Keivanpour, Hossein Safari, Mina Kazemi Miyangaskary
article en
5 citations

Abstract

The supply chain plays an essential role in the competition between companies. Supplier selection is of great importance considering the influence on the quality of the final product, the return rate, the price of the product, and the sustainability of the whole supply chain. Moreover, the real world is facing much uncertainty. In this uncertain environment, applying fuzzy decision support systems is promising. The main objective of this study is to develop an optimization model to choose suppliers and determine the number of orders for perishable protein products in uncertain conditions in a retail store. A fully fuzzy multi-objective model for a retailer company's closed-loop supply chain is developed to minimize costs and waste and maximize profit, customer satisfaction, quality, and margin under uncertainty. The proposed model is applied in a real case study of Iranian retail stores for protein products. The results proved the potential of the proposed model to improve the closed-loop supply chain's sustainability performance.

Transportation research procediaVol. 82
University of Tehran (IR), Centre Interuniversitaire de Recherche et d’Ingénierie des Matériaux (FR), Polytechnique Montréal (CA)
Openalex Percentile: Top 4%
Optimization and Mathematical Programming
6.07
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A multi-objective optimization model of a closed-loop supply chain for supplier selection and order allocation under uncertainty: A case study of retail stores for protein products — Samira Keivanpour, Hossein Safari, et al. · Transportation research procedia (2025) | TGRS Research Map | TGRS