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A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

Department of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
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Algorithms 2017, 10(3), 107; https://doi.org/10.3390/a10030107
Received: 29 June 2017 / Revised: 4 September 2017 / Accepted: 4 September 2017 / Published: 12 September 2017
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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Chen, S.; Chen, R.; Gao, J. A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem. Algorithms 2017, 10, 107.

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