摘要
在多车场车辆共享的路径优化问题中,允许多种车型的车辆同时调用,在各个车场内循环调度使用,不必回到初始发出的车场,实现一定程度的共同配送;另外,考虑满载和空载的油耗不一样,同样的路径中车辆的装载量不同成本也会不一样.要满足上述新的车辆调度要求,必须建立新的车辆调度模型:目标函数包含路径的油耗成本,约束条件中车辆不必回到原车场.由于该模型属于NP难题,因此给出了一种新的基于路径的一维编码遗传算法,通过实例证明该方法能够使车辆调度路径得到改进.
In the MDVRP system with vehicle share, the vehicles can come to any depot. And because the fuel cost becomes higher and higher, the different cost between fullload vehicle and unload vehicle can not be ignored anymore. So the new MDVRP model must meet the new situation, and the objective function must include the fuel cost of different path, and the vehicle＇s path constraints do not have to come back to the original depot. Then because the model is still a NP problem, an improved chromosome representation is proposed on the basis of path in this paper. A typical result and the analysis of experiment indicate the validity of the method to solve the MDVRP.
出处
《华中师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2010年第1期29-32,共4页
Journal of Central China Normal University：Natural Sciences
基金
湖南省教育厅基金项目(06C119)
关键词
多车型
车辆共享
路径优化
遗传算法
multiple-depot
vehicle share
vehicle routing problem
genetic algorithm
