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Efficient Transit Schedule Design of timing points: A comparison of Ant Colony and Genetic Algorithms

机译：时序点的高效公交时间表设计：蚁群算法和遗传算法的比较

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This work defines Transit Schedule Design (TSD) as an optimization problem to construct the transit schedule with the decision variables of the location of timing points and the amount of slack time associated with each timing point. Two heuristic procedures, Ant Colony and Genetic Algorithms, are developed for constructing optimal schedules for a fixed bus route. The paper presents a comparison of the fundamental features of the two algorithms. They are then calibrated based on data generated from micro-simulation of a bus route in Melbourne, Australia, to give rise to (near) optimal schedule designs. The algorithms are compared in terms of their accuracy and efficiency in providing the minimum cost solution. Although both procedures prove the ability to find the optimal solution, the Ant Colony procedure demonstrates a higher efficiency by evaluating less schedule designs to arrive at a 'good' solution. Potential benefits of the developed algorithms in bus route planning are also discussed.
机译：这项工作将公交时间表设计（TSD）定义为一种优化问题，它使用时间点的位置和与每个时间点相关的空闲时间量的决策变量来构建交通时间表。开发了两种启发式程序，即蚁群算法和遗传算法，以构建固定公交路线的最佳时间表。本文介绍了两种算法的基本特征。然后，根据在澳大利亚墨尔本的公交路线的微观模拟生成的数据对它们进行校准，以产生（接近）最佳的时间表设计。比较这些算法的准确性和效率，以提供最低成本的解决方案。尽管这两个程序都证明了找到最佳解决方案的能力，但蚁群程序通过评估较少的计划设计以达到“好的”解决方案而显示出更高的效率。还讨论了开发的算法在公交路线规划中的潜在优势。

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