Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (13): 259-262.

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Vehicle routing problem of logistics distribution based on improved particle swarm optimization algorithm

WU Cong1, YANG Jianhui2   

  1. 1.School of Computer Science and Technology, Zhoukou Normal University, Zhoukou, Henan 466001, China
    2.School of Mathematics and Statistics, Zhoukou Normal University,Zhoukou, Henan 466001, China
  • Online:2015-07-01 Published:2015-06-30

基于改进粒子群算法的物流配送车辆调度优化

吴  聪1,杨建辉2   

  1. 1.周口师范学院 计算机科学与技术学院,河南 周口 466001
    2.周口师范学院 数学与统计学院,河南 周口 466001

Abstract: Vehicle routing scheduling is an important factor to improve the operation efficiency of logistics enterprises, to solve the defects of the standard particle swarm optimization algorithm, an improved particle swarm optimization algorithm for vehicle routing problem of logistics distribution is proposed. Firstly, the mathematical model for vehicle routing problem of logistics distribution is established, and then the vehicle and vehicle routing are encoded into particles, the optimal scheme for vehicle routing problem of logistics distribution is found by the collaboration between particles in which defects of the particle swarm algorithm are improved, finally the simulation experiment is used to test the performance. The results show that the proposed algorithm not only accelerates the solving speed, but also increases the obtaining the optimal solution probability or vehicle routing problem of logistics distribution problem, and has some advantages than other scheduling algorithms.

Key words: logistics distribution, vehicle routing problem, particle swarm optimization algorithm, objection function

摘要: 车辆优化调度是提高物流企业运营效益的重要因素,针对标准粒子群优化算法存在的不足,提出一种改进粒子群算法(IPSO)的物流配送车辆调度优化方法。建立物流配送车辆调度优化的数学模型,将车辆与车辆路径编码成粒子,通过粒子之间的协作找到最优物流配送车辆调度优化方案,并对粒子群算法存在的不足进行了相应的改进,最后给出仿真实验对其性能进行测试。实验结果表明,IPSO算法不仅加快了物流配送车辆调度优化问题求解的速度,而且获得了最优解的概率,具有比其他调度算法更明显的优势。

关键词: 物流配送, 车辆路径调度问题, 粒子群算法, 目标函数