中文摘要：

列车运行调整问题是一种特殊的NP完全问题,不仅具有众多约束,并且有着列车等级要求和延迟传播限制,使得该问题搜索空间庞大,可行解范围狭小,往往难以获得较优解。为求解列车运行调整问题,针对此特殊性,将捕食搜索策略思想引入到粒子群算法中,并在此基础上提出一种速度限制的调整方式,同时辅以自适应控制,使得算法在大范围搜索时更易跳出局部最小解,而在小范围搜索时粒子飞行速度更慢,搜索更精确。将该算法用于列车运行调整问题,所得调整方案比遗传算法和普通粒子群算法结果更逼近原开行方案。

英文摘要：

As a particular NP-C problem,the train operation adjustment is hard to obtain relatively excellent solution for the huge search space and the narrow area of the feasible solution caused by numerous constraints,restrictions of propagation delay and train grade requirement. According to the particularity,this paper proposed a velocity restriction adjusting mode based on the predatory search strategy in the particle swarm optimization and combined with adaptive control. Searching in the tremendous range,the local solution could be easier to jump out,and updated the particles slower and the more accurate solution could be obtained while searching in the small range. Simulation results show that the solution by using improved PSO algorithm proposed is more approximated to the original scheme than the results solved by genetic algorithm and standard particle swarm optimization.