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Configuring a Circular Economy-based Reverse Logistics Network for the Agri-food Industry based on the Agility and Resilience Dimensions
Samaneh Valipour Khonakdari1 , Hadi Nasseri2 , Zohreh Akbari1
1- Department of Applied Mathematics, University of Mazandaran, Babolsar, Iran
2- President: Iranian Operations Research Society, Department of Applied Mathematics (Operations Research), University of Mazandaran, Babolsar, IranPresident: Research Center of Optimization and Logistic (COL), University of Mazandaran, Babolsar, Iran.Area-Editor: Fuzzy Information and Engineering Journal (FIAE)President: International Center of Optimization and Decision Making (ODM)Vice-president: International Association of Fuzzy Information and Engineering , nasseri@umz.ac.ir
Abstract:   (18 Views)
This study develops a comprehensive circular economy–based reverse logistics network for apple by explicitly integrating agility and resilience considerations under mixed uncertainty. The proposed network encompasses multiple echelons, including farms, collection centers, recycling centers, animal husbandry units, and energy and compost demand points, enabling effective waste recovery and value creation. A multi-objective mathematical programming model is formulated to simultaneously maximize economic performance, minimize node criticality as a proxy for resilience, and enhance service levels as an indicator of agility. To address the inherent uncertainty in parameters, a robust stochastic–possibilistic optimization framework is employed. Furthermore, the model is solved using a recently developed method named the Fuzzy Multi-Choice Chebyshev Goal Programming with Utility Function (FMCCGP-UF) method. The practical relevance of the proposed approach is validated through its application to a real-world case study of the apple reverse supply chain in Iran. Results reveal that increasing processing and collection capacities improve economic outcomes while simultaneously strengthening agility and resilience. The network design leads to the establishment of recycling centers #2 and #5, as well as collection centers #1, #3, and #4. Critical nodes are identified as recycling center #2 (periods 2 and 5) and collection center #1 (periods 3 and 5) and collection center #2 (periods 1 and 5). The service levels achieved are 0.73 for animal husbandry units, 0.78 for compost demand points, and 0.69 for energy demand points. Furthermore, increasing processing and collection capacities improves economic outcomes while simultaneously strengthening agility and resilience. A higher proportion of recyclable products substantially enhances value recovery and service levels, albeit with implications for node criticality.
 
Keywords: Reverse Logistics, Agri-food Reverse Logistics Industry, Agility, Resilience, Circular Economy.
Full-Text [PDF 707 kb]   (5 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2026/02/10 | Accepted: 2026/05/23
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