基于粒子群算法的城市接驳公交网络优化调度方法

    Feeder Bus Network Optimization Scheduling Method Based on Particle Swarm Optimization

    • 摘要: 为提高公共交通分担能力和解决轨道交通与交通出行起讫点之间的公共交通接驳优化调度问题,提出了轨道与公交的接驳公交网络优化模型. 模型主要考虑不同接驳站点在不同时间对轨道交通和交通出行起讫点之间的接驳需求建立多目标模型. 分析选用粒子群算法对所建立的多目标优化模型进行分析求解,比较了在轨道接驳需求下多种车队规模的调度线路、时刻安排状况,得到轨道线路邻近区域内接驳网络的优化调度,当车队规模在定值时即可满足接驳轨道交通的换乘需求,优化调度使得平均满载率显著下降,另外,验证了接驳公交网络基于粒子群算法的优化调度可有效降低营运消耗.

       

      Abstract: A feeder bus optimization scheduling model was put forward to improve the public transport sharing ability and solve bus optimization scheduling problem between rail transit and transportation origin destination in regular public transport. Different transportation demands between rail transit stations and transportation origin destination stations in different times were mainly considerate in the model, and then a multi-objective programming model was established. The multi-objective optimization model by using particle swarm optimization was analyzed and the optimal results under different situations were compared. Results show that the fixed value of buses in the team of the network optimization scheduling can meet the requirements of passengers in adjacent areas. The average load ratio is reduced significantly by using optimal operation. The viability of cost reduction of the proposed optimization model is also demonstrated.

       

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