摘要
给出了日计划机车周转图的约束满足优化问题模型及其智能求解算法，该模型以列车工作计划、机车技术作业时间、乘务员作息时间、１８点归位机车台数、检修机车最晚到达基本段时间及段备机车的最早可解备时间等作为约束条件，以减少机车在站停留时间作为目标．该模型的智能求解算法将启发式知识与回溯策略相结合，以求得日计划机车周转图的满意解．
The constraint satisfaction optimal problem model of dailyshift locomotive working diagram and its intelligent solving algorithm are given.In the model,constraints include train working plan,locomotive technical working duration,drivers' working and rest duration,the number of locomotives in the station at the end of the planning day,the due time of maintenance locomotives returning to the maintenance base, the earliest time when standby locomotives can be used,and so on.The objective is to reduce the duration of locomotives staying in stations.The intelligent algorithm combines the heuristics with backtracking strategy, and gives the satisfying solution of dailyshift locomotive working diagram.
出处
《北方交通大学学报》
CSCD
北大核心
1998年第3期57-61,共5页
Journal of Northern Jiaotong University
关键词
日计划
机车周转图
人工智能
约束满足问题
dailyshift locomotive working diagram artificial intelligence constraint satisfaction problem constraint satisfaction optimal problem
