中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2020, Vol. 39 ›› Issue (02): 35-42.DOI: 10.3969/j.issn.1674-0696.2020.02.06

• 交通运输工程 • 上一篇    下一篇

基于改进差分变邻域算法的多行程车辆路径问题的研究

宋强1,2   

  1. (1. 肇庆学院 计算机科学与软件学院、大数据学院,广东 肇庆 526061; 2. 武汉理工大学 信息工程学院,湖北 武汉 430070)
  • 收稿日期:2018-06-01 修回日期:2018-11-11 出版日期:2020-02-20 发布日期:2020-02-20
  • 作者简介:宋强(1971—),男,河南安阳人,副教授,博士,主要从事计算机控制及算法优化研究方面的工作。E-mail:gdpcit@163.com。
  • 基金资助:
    肇庆市科研创新项目(201904030404);肇庆学院校科研项目(201948)

Multi-trip Vehicle Routing Problem Based on the Improved Difference Variable Neighborhood Search Algorithm

SONG Qiang1,2   

  1. (1. School of Computer Science and Software & Big Data, Zhaoqing University, Zhaoqing 526061, Guangdong, China; 2. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China)
  • Received:2018-06-01 Revised:2018-11-11 Online:2020-02-20 Published:2020-02-20

摘要: 针对多行程车辆路径问题,先后通过标准差分进化-编码与解码-适应度计算-变邻域局部搜索过程找到最优方案,构建了一种改进差分变邻域搜索算法。该算法采用了基于轮盘赌的编码与解码方法,克服了标准差分进化算法无法适用于离散问题的缺点;同时,利用变邻域优化技术进一步强化标准差分进化算法的深度开发能力与优化性能。最后采用MATLAB中的随机函数进行仿真结果对比,验证了该算法在求解多行程车辆路径问题方面的优越性。

关键词: 交通运输工程, 多行程, 编码, 解码, 优化

Abstract: Aiming at multi-trip vehicle routing problem, the optimal solution was successively found out by standard differential evolution-encoding and decoding-fitness calculation-variable neighborhood local search procedure, and an improved difference variable neighborhood search algorithm was established. The proposed algorithm adopted the encoding and decoding method based on roulette, and overcame the shortcomings of the standard differential evolution algorithm which couldnt be applied to the discrete problem. At the same time, the depth development ability and optimization performance of the standard differential evolution algorithm were further strengthened by using the variable neighborhood optimization technique. Finally, the simulation results were compared by the random function in MATLAB, which proved the superiority of the proposed algorithm in solving the multi-trip vehicle routing problem.

Key words: traffic and transportation engineering, multi-trip, coding, decoding, optimization

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