A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem
AbstractThe 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
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Chen, S.; Chen, R.; Gao, J. A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem. Algorithms 2017, 10, 107.
Chen S, Chen R, Gao J. A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem. Algorithms. 2017; 10(3):107.Chicago/Turabian Style
Chen, Shifeng; Chen, Rong; Gao, Jian. 2017. "A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem." Algorithms 10, no. 3: 107.
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