列车行程曲线优化问题的遗传自适应A-Star方法

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI:10.1109/CIVTS.2014.7009488

Jin Huang, Lei Sun, F. Du, Hai Wan, Xibin Zhao

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引用次数: 5

摘要

研究了在一定约束条件下优化列车运行剖面的遗传自适应a星搜索算法。将列车行程曲线优化问题表述为多约束非线性优化问题，并介绍了a - star搜索算法的应用。采用NSGA-II进行A-Star搜索算法的自适应参数选择。提出了一种NSGA-II与A- star算法相结合的主结构。以一个实际的列车行程优化问题为例，说明了该方法的工作原理。

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Genetic adaptive A-Star approach for ttrain trip profile optimization problems

Genetic adaptive A-Star searching algorithm for optimizing the running profile of a train in a trip under certain constraints is studied. The train trip profile optimization problem is formulated as a multi-constraints nonlinear optimization problem, and the corresponding use of A-Star searching algorithm is introduced. NSGA-II is employed for the adaptive parameters selection of A-Star searching algorithm. A main structure with the cooperation of NSGA-II and A-Star algorithm is proposed. A practical train trip optimization problem is employed for illustrating how the proposed approach works.

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来源期刊

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)

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