基于改进量子PSO算法的可约束车辆路径优化  

Based on Quantum PSO Algorithm of Vehicle Routing Optimization Can Be Constraints

作　　者：张耀军[1] 谌昌强[1] 

机构地区：[1]信阳农林学院计算机科学系,河南信阳464000

出　　处：《计算机测量与控制》2014年第9期2875-2878,共4页Computer Measurement &Control

基　　金：河南省基础与前沿技术研究计划项目(132300410421);河南省教育厅科学技术研究重点项目(138520267)

摘　　要：为了求解有能力约束的车辆路径优化问题,提出了用于可约束车辆路径优化的改进量子PSO算法。首先给出了车辆路径的数学模型,介绍了粒子群算法;然后提出了改进量子粒子群算法,该算法采用了2-opt.1-1交换等局部优化算法那进行线路内和线路间的优化,引入种群熵算法的方法来衡量算法那是否陷入局部最优,采用灾变的操作保证解得多样性,并给出了该算法用于求解车辆路径的有关问题的具体方法;通过与别的算法的比较并结合仿真实验,有效地说明了该算法的可行性和有效性。In order to solve the problem of capacitated vehicle routing optimization, An improved quantum PSO algorithm for constrained ve- hicle routing optimization is proposed. Firstly, the mathematic model of VRP is given, the particle swarm algorithm is introduced; Then, an im- proved quantum particle swarm optimization is proposed, 2-opt and 1 - 1 opt and other local optimization algorithms are used to optimize the inner and outer route, The population entropy is introduced to check whether the algorithm is trapped into local optimization or not, and cataclysm is adopted to ensure the diversities of the solution spaces, and the detailed solving steps of VRP are given; By comparison with other algorithms and combining with simulation experiments, which effectively illustrates the feasibility and effectiveness of the algorithm.

关 键 词：量子粒子群(QPSO) 车辆路径问题 种群熵 进化计算 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]