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． This paper presents a constrained satisfaction optimization problem model and its intelligent solution algorithm for the weekly plan of the locomotive locomotive. The model takes the train work plan, the locomotive technical work time, the flight attendants’ schedule, the number of locomotives returned at 18 o’clock, the latest arrivals of the locomotive basic locomotive As well as the earliest time available for preparing locomotives, etc., as a constraint to reduce locomotive stay time at the station as a target. The intelligent algorithm of the model combines the heuristic knowledge and the backtracking strategy to find the satisfactory solution of the daily planning map.