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Erschienen in: Soft Computing 20/2017

10.03.2017 | Focus

A hybrid artificial bee colony for optimizing a reverse logistics network system

verfasst von: Jun-qing Li, Ji-dong Wang, Quan-ke Pan, Pei-yong Duan, Hong-yan Sang, Kai-zhou Gao, Yu Xue

Erschienen in: Soft Computing | Ausgabe 20/2017

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Abstract

This paper proposes a hybrid discrete artificial bee colony (HDABC) algorithm for solving the location allocation problem in reverse logistics network system. In the proposed algorithm, each solution is represented by two vectors, i.e., a collection point vector and a repair center vector. Eight well-designed neighborhood structures are proposed to utilize the problem structure and can thus enhance the exploitation capability of the algorithm. A simple but efficient selection and update approach is applied to the onlooker bee to enhance the exploitation process. A scout bee applies different local search methods to the abandoned solution and the best solution found so far, which can increase the convergence and the exploration capabilities of the proposed algorithm. In addition, an enhanced local search procedure is developed to further improve the search capability. Finally, the proposed algorithm is tested on sets of large-scale randomly generated benchmark instances. Through the analysis of experimental results, the highly effective performance of the proposed HDBAC algorithm is shown against several efficient algorithms from the literature.

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Metadaten
Titel
A hybrid artificial bee colony for optimizing a reverse logistics network system
verfasst von
Jun-qing Li
Ji-dong Wang
Quan-ke Pan
Pei-yong Duan
Hong-yan Sang
Kai-zhou Gao
Yu Xue
Publikationsdatum
10.03.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 20/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-017-2539-1

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