摘要:构建多目标改进遗传算法求解城市轨道列车运行仿真模型，求出最优运行曲线。在列车控制系统中，运行方式的转换点是基因编码的基础，由多个基因组成的染色体代表一个控制方案，通过这种方式可以形成初始种群。根据列车控制停站误差、时间误差和能耗的设计要求设计适应度函数。新个体在选择、交叉和变异过程中，通过检查原个体的有效性来保证新个体的有效性，并将最优算法加入到所有算子中，使新群体不淘汰上一代最优个体。仿真结果表明，与优化后的多粒子仿真模型相比，所提出的遗传算法可降低10%以上的能耗，可提供大量的次优解，具有明显的优化效果。关键词:多目标改进遗传算法;城市轨道列车;列车运行仿真;多粒子优化模型
Study on Optimization of Urban Rail Train Operation Control Curve Based on Improved Multi-Objective Genetic Algorithm
基于改进多目标遗传算法的城市轨道列车运行控制曲线优化研究
Abstract: A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve. In the train control system, the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme, and the initial population can be formed by the way. The fitness function can be designed by the design requ
