Travel reliability is the most essential determinant for operating the transit system and improving its service level. In this study, an optimization model for the electric transit route network design problem is proposed, under the precondition that the locations of charging depots are predetermined. Objectives are to pursue maximum travel reliability and meanwhile control the total cost within a certain range. Constraints about the bus route and operation are also considered. A Reinforcement Learning Genetic Algorithm is developed to solve the proposed model. Two case studies including the classic Mandl's road network and a large road network in the context of Zhengzhou city are conducted to demonstrate the effectiveness of the proposed model and the solution algorithm. Results suggest that the proposed methodology is helpful for improving the travel reliability of the transit network with minimal cost increase.

中文翻译：

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考虑出行可靠性的电力交通网络优化路径设计

出行可靠性是运营公交系统和提高其服务水平的最重要决定因素。在本研究中，在充电站位置预先确定的前提下，提出了电力公交线路网络设计问题的优化模型。目标是追求最大旅行可靠性，同时将总成本控制在一定范围内。还考虑了有关巴士路线和运营的限制。开发了一种强化学习遗传算法来解决所提出的模型。以郑州市为背景，通过经典曼德尔路网和大型路网两个案例研究，证明了所提出模型和求解算法的有效性。