A knowledge-based evolutionary algorithm for the multiobjective vehicle routing problem with time windows

Tsung Che Chiang*, Wei Huai Hsu

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

44 引文 斯高帕斯(Scopus)

摘要

This paper addresses the multiobjective vehicle routing problem with time windows (MOVRPTW). The objectives are to minimize the number of vehicles and the total distance simultaneously. Our approach is based on an evolutionary algorithm and aims to find the set of Pareto optimal solutions. We incorporate problem-specific knowledge into the genetic operators. The crossover operator exchanges one of the best routes, which has the shortest average distance, the relocation mutation operator relocates a large number of customers in non-decreasing order of the length of the time window, and the split mutation operator breaks the longest-distance link in the routes. Our algorithm is compared with 10 existing algorithms by standard 100-customer and 200-customer problem instances. It shows competitive performance and updates more than 1/3 of the net set of the non-dominated solutions.

原文英語
頁(從 - 到)25-37
頁數13
期刊Computers and Operations Research
45
DOIs
出版狀態已發佈 - 2014 五月

ASJC Scopus subject areas

  • 電腦科學(全部)
  • 建模與模擬
  • 管理科學與經營研究

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