A multi-cycle and multi-echelon location-routing problem for integrated reverse logistics

Abstract

Purpose

The rapid development of smart cities and green logistics has stimulated a lot of research on reverse logistics, and the diversified data also provide the possibility of innovative research on location-routing problem (LRP) under reverse logistics. The purpose of this paper is to use panel data to assist in the study of multi-cycle and multi-echelon LRP in reverse logistics network (MCME-LRP-RLN), and thus reduce the cost of enterprise facility location.

Design/methodology/approach

First, a negative utility objective function is generated based on panel data and incorporated into a multi-cycle and multi-echelon location-routing model integrating reverse logistics. After that, an improved algorithm named particle swarm optimization-multi-objective immune genetic algorithm (PSO-MOIGA) is proposed to solve the model.

Findings

There is a paradox between the total cost of the enterprise and the negative social utility, which means that it costs a certain amount of money to reduce the negative social utility. Firms can first design an open-loop logistics system to reduce cost, and at the same time, reduce negative social utility by leasing facilities.

Practical implications

This study provides firms with more flexible location-routing options by dividing them into multiple cycles, so they can choose the right option according to their development goals.

Originality/value

This research is a pioneering study of MCME-LRP-RLN problem and incorporates data analysis techniques into operations research modeling. Later, the PSO algorithm was incorporated into the crossover of MOIGA in order to solve the multi-objective large-scale problems, which improved the convergence speed and performance of the algorithm. Finally, the results of the study provide some valuable management recommendations for logistics planning.

Citation

Xu, X., Liu, W., Jiang, M. and Lin, Z. (2022), "A multi-cycle and multi-echelon location-routing problem for integrated reverse logistics", Industrial Management & Data Systems, Vol. 122 No. 10, pp. 2237-2260. https://doi.org/10.1108/IMDS-01-2022-0015