基于粒子群优化算法的钢铁企业铁路车辆调度

给出了求解铁路车辆调度问题的粒子群算法流程；分析了求解不同调度问题的3种粒子表示法，即基于粒子位置次序(Particle Position Sequence，PPS)的粒子表示法、基于粒子位置取整操作(Particle Position Rounding off，PPR)的粒子表示法和基于PPS PPR的混合粒子表示法；讨论了PPS PPR混合粒子表示法与调度解空间的映射关系和解码方法。将第3种方法应用于实际车辆调度系统中，求解出机车送货作业行驶的最短路径，建立了基于粒子群优化算法的企业铁路优化调度模型。

Study of Vehicle Optimization Scheduling System for Metallurgy Enterprise Railroad Based on Particle Swarm Optimization Algorithm

The flow procedure of particle swarm algorithm for solving railroad vehicle optimization scheduling problem was introduced, and three kinds of particle representations were analyzed, which include the particle representation based on Particle Position Sequence (PPS), the particle representation based on Particle Position Rounding off (PPR) and the hybrid particle representation based on PPS PPR. The mapping relation between particle representation based on PPS PPR and solution space of the scheduling and the decoding approaches were discussed. The third method is applied to the practical vehicle optimization scheduling system, and the shortest path for engine delivering task is solved. In the meantime, scheduling model based on the hybrid particle swarm optimization algorithm was established.