A monarch butterfly optimization for the dynamic vehicle routing problem

作者：Chen Shifeng; Chen Rong^*; Gao Jian

来源：Algorithms, 2017, 10(3): 107.

DOI：10.3390/a10030107

• Computational results
• Dynamic vehicle routing problems
• Global diversification
• Greedy strategies
• High-quality solutions
• Improve performance
• Local search
• Vehicle routing problem

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.

• 出版日期2017