Research on particle swarm optimization algorithm for train operation adjustment
面向列车运行调整问题的粒子群算法研究*

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.