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基于多目标混沌遗传算法的列车控制策略优化 被引量:4

Train Control Strategy Optimization Based on Multi-objective Chaotic Genetic Algorithm
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摘要 为得到一组满意的行车控制策略,构建了列车运行多目标模型,并以列车运行动力学模型为基础求得列车局部运行控制策略制定方法。使用基于混沌优化的多目标遗传算法对列车控制策略进行优化研究,以相位转换点作为基因序列,多个基因组成染色体形成一套控制策略。使用混沌初始化种群,结合精英保留策略,增加了种群的多样性,并提高算法收敛能力。最后采用Matlab软件仿真验证了方法的可行性及有效性。 In order to get satisfying train control strategy, a multi-objective model is established. Found the method for constitute train control strategy based on train dynamics model, used operation was established with train dynamics model. Chaotic optimization based multi-objective optimization genetic algorithm is used to optimize strate- gy of train control. Phase transition point as gene sequences in GA, each chromosome formed by genes composes a set of control strategy, using the chaos to initialize population combines the elitist preserve strategy, the population diversity has improved and the convergence ability of algorithm has enhanced. At last the feasibility and effective- ness are proved with the results simulated on Matlab.
作者 苗渤汶 李华
出处 《科学技术与工程》 北大核心 2013年第11期3167-3171,共5页 Science Technology and Engineering
关键词 列车控制策略 多目标优化 遗传算法 混沌 train control strategy multi-objective optimization genetic algorithm chaos
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