中国机械工程

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多车场与多车型车辆路径问题的多染色体遗传算法

陈呈频;韩胜军;鲁建厦;陈青丰;王成   

  1. 浙江工业大学工业工程研究所,杭州,310014
  • 出版日期:2018-01-25 发布日期:2018-01-22
  • 基金资助:
    浙江省自然科学基金资助项目(LY15G010009)
    Zhejiang Provincial Natural Science Foundation of China (No. LY15G010009)

A Multi-chromosome Genetic Algorithm for Multi-depot and Multi-type Vehicle Routing Problems

CHEN Chengpin;HAN Shengjun;LU Jiansha;CHEN Qingfeng;WANG Cheng   

  1. Industry Engineering Institute,Zhejiang University of Technology,Hangzhou,310014
  • Online:2018-01-25 Published:2018-01-22
  • Supported by:
    Zhejiang Provincial Natural Science Foundation of China (No. LY15G010009)

摘要: 针对目前多车场、多车型车辆路径问题存在的求解效率低和解的质量差等不足,建立了该问题的整数规划模型,提出了多染色体遗传算法,统一了多车场、多车型问题与传统单车场、单车型问题的求解算法。通过算例对多染色体遗传算法进行了实验,并将其与传统算法进行了对比分析。实验表明,该算法不仅呈现出搜索效率高和收敛速度快的特点,而且解的质量和稳定性高,从而验证了算法的有效性和实用性。

关键词: 车辆路径问题, 多车场, 多车型, 遗传算法, 多染色体

Abstract: Aiming at shortcomings of low efficiency and poor quality of solutions in the current multi-depot and multi-type vehicle routing problems, an integer programming model was established. A multi-chromosome genetic algorithm was proposed to unify the solution algorithms of the multi-depot and multi-vehicle problems, and traditional single depot and single vehicle problems. Several experiments were completed on the multi-chromosome genetic algorithm through calculation examples, and comparisons with the traditional algorithm results were carried out. Experiments show that the proposed algorithm exhibits high search efficiency and fast convergence speed, and has high quality and stability of the solutions, which verify effectiveness and practicability of the algorithm.

Key words: vehicle routing problem, multi-depot, multi-type, genetic algorithm, multi-chromosome

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