混编公交发车间隔及车辆运用计划协同优化的两阶段模型
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华东交通大学

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国家自然科学基金资助项目(71801093)


A two-stage model for collaborative optimization of mixed bus departure intervals and vehicle utilization plans
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The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    本文的主要研究内容为由燃油公交和电动公交共同组成的混编公交发车间隔与车辆运用计划协同优化,以发车间隔平滑化程度和综合运营成本最小为优化目标,考虑发车间隔范围、车辆数目、车辆接续、电动公交续航里程等多个约束,建立优化模型。设计遗传算法对两阶段模型进行求解,提升了求解的效率与准确性。案例表明:和既有运营方案相比,此优化模型可以在较为均匀的发车间隔下,合理配置公交车辆使用数目,实现电动公交错峰充电,提升车辆利用率,节约车辆总运营成本可达到13.04%。

    Abstract:

    The main research focus of this study is the collaborative optimization of mixed-operation bus departure intervals and vehicle utilization plans, involving both fuel-powered and electric buses. The optimization objectives are to achieve smooth departure intervals and minimize overall operational costs. Multiple constraints are considered, including departure interval range, number of vehicles, vehicle connectivity, and electric bus range. An optimization model is established to address these aspects. A genetic algorithm is designed to solve the two-stage model, enhancing efficiency and accuracy of the solution. The case demonstrate that compared to the existing operating scheme, this optimization model can allocate the number of buses used more reasonably with a relatively uniform departure interval. It achieves off-peak charging for electric buses, enhances vehicle utilization, and saves up to 13.04% of the total operational cost of vehicles.

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历史
  • 收稿日期:2023-07-11
  • 最后修改日期:2023-08-13
  • 录用日期:2023-08-22
  • 在线发布日期: 2024-03-26
  • 出版日期: