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Bus Dispatching Interval Optimization Based on Adaptive Bacteria Foraging Algorithm

机译:基于自适应细菌觅食算法的公交调度区间优化

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摘要

The improved bacterial foraging algorithm was applied in this paper to schedule the bus departing interval. Optimal interval can decrease the total operation cost and passengers' mean waiting time. The principles of colony sensing, chemotactic action, and improved foraging strategy made this algorithm adaptive. Based on adaptive bacteria foraging algorithm (ABFA), a model on one bus line in Hohhot city in China was established and simulated. Two other algorithms, original bacteria foraging algorithm (BFA) and genetic algorithm (GA), were also used in this model to decide which one could greatly accelerate convergence speed, improve searching precision, and strengthen robustness. The final result showed that ABFA was most feasible in optimizing variables.
机译:本文采用改进的细菌觅食算法来调度公交车的发车间隔。最佳间隔可以减少总运营成本和乘客的平均等待时间。菌落感测,趋化作用和改进的觅食策略使该算法具有自适应性。基于自适应细菌觅食算法(ABFA),建立并模拟了呼和浩特市一条公交线路的模型。该模型还使用其他两种算法,即原始细菌觅食算法(BFA)和遗传算法(GA)来确定哪种算法可以极大地加快收敛速度​​,提高搜索精度并增强鲁棒性。最终结果表明,ABFA在优化变量方面最可行。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第11期|389086.1-389086.10|共10页
  • 作者单位

    Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China;

    Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China;

    Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China;

    Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China;

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