Sustainable p-hub Median Modeling for Perishable items in presence of Fuzzy Setting

Subject Areas : Mathematical Optimization

saeed zameni ¹ , Esmaeil Najafi ² , seyyed mohammad Hadjimolana ³ , Seyed Mojtaba Sajadi ⁴

1 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
4 - Operations and Information Management Department, Aston Business School, Aston University, Birmingham, B4, 7ET, UK

Received: 2022-08-22 Accepted : 2024-08-29 Published : 2024-09-05

Keywords: Food supply chain, Fuzzy multi-objective nonlinear programming, P-hub median problem, perishability, Sustainable supply chain,

Abstract :

Considering the social and environmental impacts, the purpose of this paper is to present a new sustainable hub location model for perishable items similar to real world in which the transport time between nodes is fuzzy numbers. For the first time, time uncertainty in a sustainable hub location problem of a perishable product is considered in this study. Demands from the nodes of each hub are collected in that hub and sent to the hub to which the destination node is allocated and finally reach the destination node. This multi objective model considers the perishability of products for distribution in a food supply chain and with regard to cost reduction. It takes into account CO2 emissions and the social impact by increasing jobs resulting from locating the hub in nodes with low employment rates of the hub network simultaneously. This problem is modeled as a nonlinear programming of multi-objective mixed integers that optimizes total transportation costs, freshness and quality of food at carbon delivery and emission, and social effects to achieve sustainability. The model has been solved and validated in small and medium size with GAMS software. The results show that considering social responsibility factor leads to a change in location and allocation network design that increases objective function.

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