Designing the Location–Routing Problem for a Cold Supply Chain Considering the COVID-19 Disaster

Sina Abbasi, Maryam Moosivand, Ilias Vlachos () and Mohammad Talooni
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Sina Abbasi: Department of Industrial Engineering, Lahijan Branch, Islamic Azad University, Lahijan 1616, Iran
Maryam Moosivand: Institute for Management and Planning Studies, Tehran 1411713135, Iran
Ilias Vlachos: Excelia Business School, Excelia Group, 17000 La Rochelle, France
Mohammad Talooni: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran 141556311, Iran

Sustainability, 2023, vol. 15, issue 21, 1-24

Abstract: In this study, a location routing problem (LRP) model was considered for the distribution network of multiple perishable food items in a cold supply chain (CSC) where vehicles can refuel at gas stations during light of the COVID-19 disaster. Fuel consumption is assumed to vary depending on the cargo transported between nodes when using a non-standard fuel fleet. The problem was formulated as a mixed-integer linear programming (MILP) model to reduce the production of carbon dioxide (CO 2 ). The model was validated using several numerical examples which were solved using the software, LINGO 17.0. The results show that fuel consumption could be reduced in this case. Due to the complexity of the problem, genetically simulated annealing algorithms were developed to solve the actual size problems, and their performance was also evaluated.

Keywords: sustainable supply chain; COVID-19 disaster; cold logistics; CO 2 emissions; location routing problem; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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