基于种群分类粒子群算法的物流车辆调度优化  

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

作　　者：邓先瑞[1] 于晓慧[1] 李春艳[1] 赵光峰[2] 

机构地区：[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　　处：《计算机工程与应用》2016年第10期237-240,258,共5页Computer Engineering and Applications

基　　金：河北省科技计划项目(No.13220319D);唐山师范学院博士基金项目(No.07A01)

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。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.

关 键 词：配送车辆 粒子群算法 种群分类 调度方案 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]