摘要
针对动态需求下的带时间窗的车辆路径问题,在最小化配送成本的目标下,通过提升服务的准时性来改进顾客满意度。考虑两阶段规划策略:在初始规划阶段,采用改进的遗传算法获得初始车辆路径;在动态优化阶段,将动态需求过程转化为多个瞬时静态子过程,采用模拟退火算法得到实时优化后的车辆路径方案。在一个实际案例中的应用和求解,证明了方法的现实有效性。
A vehicle routing problem with time windows based on dynamic demand was examined aiming at total dispatching cost minimization.Service punctuality was especially considered to improve customer satisfaction.With a two-stage strategy,a modified genetic algorithm was applied to get initial vehicle routing in the stage of initial routing programming.The dynamic demand process was then transformed into several momentary static sub-processes in the second stage of dynamic optimization,and a simulated annealing algorithm was used to obtain the final solutions.A real case study then was followed to illustrate the validity of this approach.
出处
《工业工程与管理》
CSSCI
北大核心
2016年第6期68-74,共7页
Industrial Engineering and Management
基金
国家自然科学基金资助重大项目(71390331)
国家自然科学基金资助面上项目(71371151)
教育部人文社会科学研究规划基金资助项目(13YJA630078)
关键词
动态需求
车辆路径问题
软时间窗
启发式算法
dynamic demand
vehicle routing problem
soft time window
heuristic algorithms
