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Timetable optimization for single bus line involving fuzzy travel time

机译:用于涉及模糊行程时间的单母线线的时间表优化

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Timetable optimization is an important step for bus operations management, which essentially aims to effectively link up bus carriers and passengers. Generally speaking, bus carriers attempt to minimize the total travel time to reduce its operation cost, while the passengers attempt to minimize their waiting time at stops. In this study, we focus on the timetable optimization problem for a single bus line from both bus carriers’ perspectives and passengers’ perspectives. A bi-objective optimization model is established to minimize the total travel time for all trips along the line and the total waiting time for all passengers at all stops, in which the bus travel times are considered as fuzzy variables due to a variety of disturbances such as weather conditions and traffic conditions. A genetic algorithm with variable-length chromosomes is devised to solve the proposed model. In addition, we present a case study that utilizes real-life bus transit data to illustrate the efficacy of the proposed model and solution algorithm. Compared with the timetable currently being used, the optimal bus timetable produced from this study is able to reduce the total travel time by 26.75% and the total waiting time by 9.96%. The results demonstrate that the established model is effective and useful to seek a practical balance between the bus carriers’ interest and passengers’ interest.
机译:时间表优化是巴士运营管理的重要一步,基本上旨在有效地联系起船运营商和乘客。一般来说,巴士运营商试图最大限度地减少总旅行时间以降低其运营成本,而乘客试图将他们的等待时间最小化在停止时。在这项研究中,我们专注于从总线运营商的透视和乘客的观点的单一总线的时间表优化问题。建立了双目标优化模型,以最大限度地减少所有沿线的所有旅行的总旅行时间和所有停止的所有乘客的总等待时间,其中总线旅行时间被认为是由于各种干扰导致的模糊变量作为天气条件和交通状况。设计了一种具有可变长度染色体的遗传算法来解决所提出的模型。此外,我们提出了一种案例研究,它利用现实寿命总线传输数据来说明所提出的模型和解决方案算法的功效。与目前正在使用的时间表相比,本研究生产的最佳总线时间表能够将总旅行时间减少26.75%,总等待时间为9.96%。结果表明,既定的模型是有效的,可用于寻求公交车辆兴趣和乘客兴趣之间的实际平衡。

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