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Multi‐objective location‐routing problem of reverse logistics based on GRA with entropy weight

Hong Liu (School of Management, Fuzhou University, Fuzhou, China)
Wenping Wang (Department of Management Science and Engineering, The Southeast University of Economics and Management, Nanjing, China)
Qishan Zhang (Department of Management Science and Engineering, The Fuzhou University of Management, Fuzhou, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 17 August 2012

527

Abstract

Purpose

The purpose of this paper is to realize a multi‐objective location‐routing network optimization in reverse logistics using particle swarm optimization based on grey relational analysis with entropy weight.

Design/methodology/approach

Real world network design problems are often characterized by multi‐objective in reverse logistics. This has recently been considered as an additional objective for facility location problem or vehicle routing problem in reverse logistics network design. Both of them are shown to be NP‐hard. Hence, location‐routing problem (LRP) with multi‐objective is more complicated integrated problem, and it is NP‐hard too. Due to the fact that NP‐hard model cannot be solved directly, grey relational analysis and entropy weight were added to particle swarm optimization to decision among the objectives. Then, a mathematics model about multi‐objective LRP of reverse logistics has been constructed, and a proposed hybrid particle swarm optimization with grey relational analysis and entropy weight has been developed to resolve it. An example is also computed in the last part of the paper.

Findings

The results are convincing: not only that particle swarm optimization and grey relational analysis can be used to resolve multi‐objective location‐routing model, but also that entropy and grey relational analysis can be combined to decide weights of objectives.

Practical implications

The method exposed in the paper can be used to deal with multi‐objective LRP in reverse logistics, and multi‐objective network optimization result could be helpful for logistics efficiency and practicability.

Originality/value

The paper succeeds in realising both a constructed multi‐objective model about location‐routing of reverse logistics and a multi‐objective solution algorithm about particle swarm optimization and future stage by using one of the newest developed theories: grey relational analysis.

Keywords

Citation

Liu, H., Wang, W. and Zhang, Q. (2012), "Multi‐objective location‐routing problem of reverse logistics based on GRA with entropy weight", Grey Systems: Theory and Application, Vol. 2 No. 2, pp. 249-258. https://doi.org/10.1108/20439371211260216

Publisher

:

Emerald Group Publishing Limited

Copyright © 2012, Emerald Group Publishing Limited

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