摘要
针对行驶受扰延迟下配送车辆的调度问题,提出了基于多相量子粒子群算法的两阶段干扰管理决策方法.首先以最小化用户时间窗偏离度和最小化配送成本为目标,建立了问题的数学模型;然后对车辆配送发生干扰事件可能采取的干扰管理模式进行了归纳和分类,并在选定模式基础上提出了用多相量子粒子群算法进行路线选择的方法;最后在Solomon算例的基础上通过实验仿真,对所提出方法的性能进行测试,并与全局重调度方法进行对比分析,验证了本文方法不仅达到了优化目标的目的,还满足了干扰管理的实用性要求.
In order to solve the vehicle scheduling problem with traffic disruption delay,a two-stage disruption management method based on multi-phase quantum particle swarm optimization(MQPSO)is proposed.Firstly,a mathematical model of the problem is established to minimize the time window deviation and minimize the distribution cost.Next,the possible disruption management mode of distribution vehicles is summarized and classified and the route scheduling method is proposed on the basis of selected mode.At last,the simulation experiments are executed based on the Solomon example to test the performance of the proposed method.The effectiveness and practicability of the proposed method is verified through the comparison and analysis with rescheduling method.
作者
宁涛
王旭坪
胡祥培
NING Tao;WANG Xuping;HU Xiangpei(Institute of Software,Dalian Jiaotong University,Dalian 116054,China;Institute of Systems Engineering,Dalian University of Technology,Dalian 116023,China)
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2019年第5期1236-1245,共10页
Systems Engineering-Theory & Practice
基金
国家自然科学基金重点项目(71531002)
国家自然科学基金(71471025)
中国博士后科学基金(2017M611231)~~
关键词
受扰延迟
干扰管理
救援模式
多相量子粒子群算法
disruption delay
disruption management
rescue model
multi-phase quantum particle swarm algorithm
