交通运输系统工程与信息 ›› 2009, Vol. 9 ›› Issue (1): 80-86 .

• 系统工程理论与方法 • 上一篇    下一篇

城市公交服务网络能力计算研究

赵航; 何世伟* ; 宋瑞   

  1. 北京交通大学 交通运输学院, 北京 100044
  • 收稿日期:2008-03-10 修回日期:2008-06-18 出版日期:2009-02-25 发布日期:2009-02-25
  • 通讯作者: 何世伟
  • 作者简介:赵航(1981-),男,贵州贵阳人,博士生.
  • 基金资助:

    863项目“国家高技术研究发展计划”(2006AA11A203);霍英东教育基金会有选项目(104007);北京交通大学重点基金(2006XZ004).

Modeling Service Network Capacity for Urban Public Transport

ZHAO Hang; HE Shi-wei; SONG Rui   

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China
  • Received:2008-03-10 Revised:2008-06-18 Online:2009-02-25 Published:2009-02-25
  • Contact: HE Shi-wei

摘要: 构建了公交服务网络,定义了公交服务网络总体能力、总体有效能力、潜在能力和无效能力的概念,分析了公交服务网络能力的影响因素;考虑各影响因素对公交服务网络能力的影响,建立了公交服务网络总体有效能力模型,同时给出基于遗传算法的求解算法;针对大规模混合整数规划采用遗传算法进行求解可以提高求解效率,通过相关案例对模型和算法的可行性和有效性进行了检验。实例计算表明,该算法在处理混合整数规划具有一定的实用性,为进一步深入研究公交服务网络能力奠定基础。

关键词: 交通工程, 城市公共交通, 服务网络能力, 有效能力, 遗传算法

Abstract: In this paper, the service network for urban public transport is constructed; besides, the concepts of total capacity, total effective capacity, potential capacity and noneffective capacity of the service network for urban public transport are also proposed. In addition, the key factors to the service network capacity for urban public transport are analyzed. The model for the total effective capacity of the service network for urban public transport is formulated according to the key factors to the service network capacity for urban public transport. The computational approach based on the genetic algorithm is provided and the efficiency of the solution is improved by the genetic algorithm to large sizes of mixed integer programming. The feasibility and effectiveness of the model and the algorithm were testified by the experimental example, and it showed that the practicability of the algorithm to mixed integer programming has set a foundation for further research of the service network capacity for urban public transport.

Key words: traffic engineering, urban public transport, service network capacity, effective capacity, Genetic algorithm

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