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Algorithms 2017, 10(3), 107; doi:10.3390/a10030107

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

Department of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
Authors to whom correspondence should be addressed.
Received: 29 June 2017 / Revised: 4 September 2017 / Accepted: 4 September 2017 / Published: 12 September 2017
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The dynamic vehicle routing problem (DVRP) is a variant of the Vehicle Routing Problem (VRP) in which customers appear dynamically. The objective is to determine a set of routes that minimizes the total travel distance. In this paper, we propose a monarch butterfly optimization (MBO) algorithm to solve DVRPs, utilizing a greedy strategy. Both migration operation and the butterfly adjusting operator only accept the offspring of butterfly individuals that have better fitness than their parents. To improve performance, a later perturbation procedure is implemented, to maintain a balance between global diversification and local intensification. The computational results indicate that the proposed technique outperforms the existing approaches in the literature for average performance by at least 9.38%. In addition, 12 new best solutions were found. This shows that this proposed technique consistently produces high-quality solutions and outperforms other published heuristics for the DVRP. View Full-Text
Keywords: monarch butterfly optimization; dynamic vehicle routing problem; greedy strategy; local search monarch butterfly optimization; dynamic vehicle routing problem; greedy strategy; local search

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, S.; Chen, R.; Gao, J. A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem. Algorithms 2017, 10, 107.

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