摘要
针对动态车辆路径中出现新的客户请求时,输入信息(可能包括客户请求出现时的车辆位置、客户时间窗、服务时间、需求量等)也随着时间推移而动态改变,在服务客户时由于动态客户需要不停插入,导致不停地进行优化计算,致使车辆路径更新频繁的问题,提出了紧急动态客户和数据包的概念(简称ICP)。通过该策略并使用遗传方法(Genetic Algorithm,GA)与局部搜索方法(Local Search,LS)的混合算法(简称GA-LS),可提高车辆路径更新质量,降低车辆运输成本并控制配送中心管理成本,从而提高服务质量。通过实验证明了该策略的有效性。
For the new customer requests that appear in the dynamic vehicle path, the input information （which may include the location of the vehicle when the customer request appears, the customer＇s time window, service time, demand, etc. ） changes dynamically over time. In the service of customers, due to frequently inserting of dynamic customers＇ demand and the vehicle path updating ,which leads to the none-stop optimal calculation. In this paper, the concept of emergency dynamic customer and data packet （ICP） is proposed. Through using this strategy and GA-LS method , the transportation cost of vehicle is reduced and the management cost of distribution center is controlled, then the quality of service is optimized. The validity of the ICP method is proved By experiments.
出处
《软件导刊》
2018年第3期172-175,共4页
Software Guide
