混合遗传算法求解配送车辆调度问题  

Hybrid genetic algorithm for distribution vehicle routing problem

作　　者：曲倩倩[1] 曲仕茹[1] 温凯歌[1] 

机构地区：[1]西北工业大学自动化学院,西安710072

出　　处：《计算机工程与应用》2008年第15期205-207,227,共4页Computer Engineering and Applications

基　　金：国家自然科学基金重点支持项目(No.60134010)

摘　　要：车辆调度优化是物流配送的关键环节。针对有时间窗的车辆调度问题,综合考虑了路网中的交通状况,提出改进的车辆调度模型。并针对这个模型,设计了混合遗传算法,采用自适应策略调整交叉和变异概率,引进有效的交叉和变异算子,并结合模拟退火算法缓解遗传算法的选择压力,避免早熟收敛。仿真结果表明该算法与标准遗传算法相比有更好的性能。The optimization of vehicle routing is the focus of the logistic distribution.Aiming at solving the vehicle routing problem with time windows,an improved vehicle routing model is built under the consideration of the traffic status.A hybrid genetic algorithm is proposed based on the model above and the self-adaptive strategies are introduced to adjust the parameters of crossover and mutation.Effective crossover and mutation operators are also adopted in the algorithm.Moreover,in order to relieve the selecting pressure,the simulated annealing algorithm is combined with the genetic algorithm and consequently the global convergence has been greatly improved.Results of the simulation show that the proposed algorithm is more efficient compared with the classic genetic algorithm.

关 键 词：车辆调度问题 混合遗传算法 自适应策略 路阻函数 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]