An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network

Abstract

The transition to sustainable supply chains in industries where perishable products are prominent requires advanced models for logistics management. In this paper, a model of integrated location, routing, and inventory problem, the three key problems in optimizing a logistics system, is introduced. Considering the particular decision-making environment of such industries, we give a two-phase approach to incorporate the three dimensions of sustainability into supply chain practices. After identifying more sustainable-oriented suppliers, a problem is formulated as a multi-objective Mixed-Integer Programming (MIP) model to assist in planning a sustainable supply chain. Based on the proposed two-phase approach, we contribute to the current literature by simultaneously addressing different challenges, e.g., sustainability issue, integrated decision-making on location, routing, and inventory control planning, and real-world assumptions to make further advances in both research and practice. Since finding the optimal solution for this problem is a NP-hard problem, two hybrid metaheuristics as parallel and series combinations of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are utilized to solve the problem. The implementation of a set of test instances demonstrates the superiority of the parallel hybridization over the series one. Furthermore, it is observed that when the goal of sustainability is approached, manufacturing sector tends to be decentralized and the local commodity production in more medium- and low-developed locations can exhibit the best sustainability performance.