摘要
为了使网络中的车辆调度问题更加符合实际交通状况,针对时变网络中的车辆调度问题进行了研究。将传统车辆调度模型进行了修改,目标函数中考虑了车辆的总行驶费用、总迟到惩罚、车辆总启用费用3种因素,以提高模型的适应性和通用性。由于车辆调度问题属于NP难问题,提出了采用遗传算法对问题进行求解。采用标准的VRP问题进行测试,仿真结果表明该算法简单可行,较BC-Saving启发式算法有更好的求解性能。
In order to accord with the actual traffic status in road networks,vehicle routing problem with time dependent travel time is researched.The authors modify the traditional vehicle scheduling model,total vehicle expense,total delay penahy,total vehicle use expenses are considered in the objective,so as to improve the applicability and universality of model.Since vehicle scheduling problem is NP-hard,parallel genetic algorithm is proposed to solve this problem.In order to verify the effectiveness of the parallel genetic algorithm,stand VRP problems are used.The simulation results show that the algorithm is very easy and feasible and compared with BC-Saving algorithm,it has rapid convergence ability and searching ability.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第22期210-212,共3页
Computer Engineering and Applications
基金
天津市科技支撑计划项目(No08ZCKFGX01500)
中国民航大学科研启动基金(No06qd02x)
关键词
车辆派遣
时变
动态
遗传算法
vehicle routing problem
time dependent
dynamic
genetic algorithm
