《计算机应用研究》|Application Research of Computers

基于不确定需求的公共交通网络鲁棒性优化方法

Robust optimization method for public transport network based on uncertain demand

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作者 周康,宋瑞,彭虓
机构 1.交通运输部科学研究院,北京 100029;2.北京交通大学 城市交通复杂系统理论与技术教育部重点实验室,北京 100044
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文章编号 1001-3695(2020)07-017-2006-05
DOI 10.19734/j.issn.1001-3695.2018.12.0935
摘要 为了提高城市不同类型公共交通所组成的线网的鲁棒性,从公共交通线路建设成本、乘客出行的总时间以及乘客总换乘次数等方面确定公共交通网络的服务性能模型,在此基础上通过计算方案目标值与期望值的差值来确定公交网络的鲁棒性;由于存在随机不确定需求,在传统免疫克隆算法基础上对变异操作进行改进,用于对优化模型求解。结合算例分析发现,线路建设成本、乘客总出行时间以及乘客总换乘次数的参数值对于优化结果具有显著影响;另外鲁棒性参数取值也会对计算结果产生一定影响,通过算例验证了优化方法的可行性。
关键词 城市交通; 鲁棒性优化; 免疫克隆算法; 公共交通网络; 不确定需求
基金项目 国家自然科学基金资助项目(41471459)
国家重点研发计划项目(2018YFB1600900)
国家科技支撑计划资助项目(2018YFB1201402)
本文URL http://www.arocmag.com/article/01-2020-07-017.html
英文标题 Robust optimization method for public transport network based on uncertain demand
作者英文名 Zhou Kang, Song Rui, Peng Xiao
机构英文名 1.China Academy of Transportation Sciences,Beijing 100029,China;2.MOE Key Laboratory for Urban Transportation Complex Systems Theory & Technology,Beijing Jiaotong University,Beijing 100044,China
英文摘要 In order to improve the robustness of the network composed of different modes of urban public transport, from the aspects of construction cost of public transport line, total travel time of passengers and total transfer times of passengers to construct the service performance model of public transport network. On this basis, it determined the robustness of the public transport network by calculating the D-value between the target value and the expected value. Due to the existence of uncertain demand, this paper improved the mutation operation based on the traditional immune clonal algorithm to solve the optimization model. It is found that the parameters of route construction cost, total passenger travel time and total passenger transfer times have a significant impact on the optimization results. In addition, the robustness parameters also have a certain impact on the calculation results. From the case study, it verifies the feasibility of the optimization method and found some problems that need to be improved.
英文关键词 urban traffic; robust optimization; immune clonal algorithm; public transport network; uncertain demand
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收稿日期 2018/12/27
修回日期 2019/3/4
页码 2006-2010
中图分类号 U491.1+7;TP301.6
文献标志码 A