隔离小生境粒子群算法在地铁列车运行曲线优化中的应用

Application of Isolation Niche Particle Swarm Optimization in Optimization of Subway Train Operation Curve

针对地铁列车运行优化指标过于单一的问题,提出了牵引-巡航-惰行-制动模式运行曲线的计算流程,综合考虑能耗、乘客舒适度、运行时间、停车精度等指标,用Fi(综合优化目标函数)值度量综合运行质量(其值越小表示越接近理想状态),并建立列车运行曲线的优化模型。结合粒子群算法和小生境技术,设计了应用于列车运行曲线优化的隔离小生境粒子群算法(INPSO)。结合实例仿真,利用INPSO优化模型,确定最优惰行末端速度,实现了高质量列车运行曲线的计算。其中INPSO优化后的Fi值实际只是基本粒子群算法优化结果的58.96%,效果显著,证明了INPSO寻优的有效性以及可靠性。

Aiming at the extremely simple performance indexes of metro train operation optimization,a calculation flow of train operation curve with ＂traction-crusing-coasting-braking ＂mode is proposed,the energy consumption,passengers comfort,operation time,parking precision are taken into comprehensive consideration,the value Fiis used to comprehensively measure the operation quality（ the smaller Fimeans the closer to ideal state）, and an optimization model is established.Combined with niche particle sw arm optimization（ INPSO）and isolation technology,the niche particle sw arm optimization（INPSO） to be applied in optimization of train operation curve is designed. Then,based on an instance simulation,the model is optimized by IPSO,coasting terminal velocity is determined and the calculation of subway train optimum operation curve with high quality is completed. The value Fioptimized by INPSO is about 58. 96% of the optimization result in basic particle w arm algorithm,verifying the remarkable effect,the validity and reliability of INPSO.