计算机工程与应用 ›› 2016, Vol. 52 ›› Issue (10): 237-240.

• 工程与应用 • 上一篇    下一篇

基于种群分类粒子群算法的物流车辆调度优化

邓先瑞1,于晓慧1,李春艳1,赵光峰2   

  1. 1.唐山师范学院 计算机科学系,河北 唐山 063000
    2.唐山师范学院 科研处,河北 唐山 063000
  • 出版日期:2016-05-15 发布日期:2016-05-16

Vehicle scheduling optimization method based on particle swarm optimization algorithm with population classification

DENG Xianrui1, YU Xiaohui1, LI Chunyan1, ZHAO Guangfeng2   

  1. 1.Department of Computer Science, Tangshan Normal University, Tangshan, Hebei 063000, China
    2.Department of Research, Tangshan Normal University, Tangshan, Hebei 063000, China
  • Online:2016-05-15 Published:2016-05-16

摘要: 为了获得更加理想的配送车辆调度方案,提出一种基于种群分类粒子群算法的配送车辆调度优化方法。首先建立多约束配送车辆调度的数学模型,并以配送路径最短作为目标函数,然后采用粒子群算法对模型进行求解,并对每次迭代产生的粒子群进行分类,根据分类结果对粒子群进行不同的操作,加快了算法的搜索速度,以避免陷入局部最优,最后进行仿真对比实验。结果表明,种群分类粒子群算法获得比较理想的配送车辆调度方案,具有一定的实用价值。

关键词: 配送车辆, 粒子群算法, 种群分类, 调度方案

Abstract: In order to obtain good vehicle scheduling results, a vehicle scheduling optimization method based on particle swarm optimization algorithm with population classification is proposed in this paper. Firstly, a mathematical model of vehicle scheduling problem is established, and then the model is solved by improved particle swarm optimization algorithm which particle swarms have different operations according to the classification results to speed up the search speed and avoid falling into local optimal, finally, the simulation experiment is used to test the performance. The result shows that the proposed particle swarm optimization algorithm can obtain good vehicle scheduling solution, and it has certain practical value.

Key words: vehicle distribution, particle swarm optimization algorithm, population classification, scheduling scheme