A Discrete Artificial Bee Colony Algorithm for the Reverse Logistics Location and Routing Problem

Kun Guo () and Qishan Zhang ()
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Kun Guo: College of Mathematics and Computer Science, Fuzhou University, 2 Xue Yuan Road, Fuzhou Fujian 350108, China
Qishan Zhang: School of Management, Fuzhou University, 2 Xue Yuan Road, Fuzhou Fujian 350108, China

International Journal of Information Technology & Decision Making (IJITDM), 2017, vol. 16, issue 05, 1339-1357

Abstract: Reverse logistics (RL) emerges as a hot topic in both research and business with the increasing attention on the collection and recycling of the waste products. Since Location and Routing Problem (LRP) in RL is NP-complete, heuristic algorithms, especially those built upon swarm intelligence, are very popular in this research. In this paper, both Vehicle Routing Problem (RP) and Location Allocation Problem (LAP) of RL are considered as a whole. First, the features of LRP in RL are analyzed. Second, a mathematical model of the problem is developed. Then, a novel discrete artificial bee colony (ABC) algorithm with greedy adjustment is proposed. The experimental results show that the new algorithm can approach the optimal solutions efficiently and effectively.

Keywords: Artificial bee colony (ABC); reverse logistics; location and routing problem (LRP) (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0219622014500126

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