交通运输系统工程与信息 ›› 2009, Vol. 9 ›› Issue (5): 90-95 .

• 系统工程理论与方法 • 上一篇    下一篇

基于多目标优化的道路客运站场选址研究

郝合瑞1;邵春福*1;岳昊1,2;段龙梅3   

  1. 1 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;
    2 北京工业大学 交通研究中心,北京 100022;3. 吉林省公路勘测设计院,长春 130021
  • 收稿日期:2009-06-28 修回日期:2009-09-01 出版日期:2009-10-25 发布日期:2009-10-25
  • 通讯作者: 邵春福
  • 作者简介:郝合瑞(1964-),男,河北廊坊人,工程师,博士生.
  • 基金资助:

    国家重点基础研究发展计划(973计划)( 2006CB705500)

Location of Road Passenger Transportation Hub Based on Multi-Objective Optimization

HAO He-rui1;SHAO Chun-fu1; YUE Hao 1,2; DUAN Long-mei3   

  1. 1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China; 2. Transportation Research Center, Beijing University of Technology, Beijing 100022, China;
    3. Jilin Provincial Highway Survey and Design Institute, Changchun 130021, China
  • Received:2009-06-28 Revised:2009-09-01 Online:2009-10-25 Published:2009-10-25
  • Contact: SHAO Chun-fu

摘要: 为了研究道路客运站场规划的站场选址优化,提出了一种基于多目标优化的道路客运站场选址方法。首先,将道路客运站场规划区域的道路网简化为有向赋权图,使选址优化问题转化为0-1规划问题;然后,以道路客运站场的建设投资、网络总运输成本以及乘客的总出行距离为优化目标,同时把道路客运的实际条件转化为优化目标的约束条件;最后,利用基于目标值排序组合选择的多目标遗传算法求解模型的Pareto最优解集合,并通过客运站场选址优化算例阐述了模型的求解过程。

关键词: 交通工程, 站场选址, 多目标优化, 遗传算法

Abstract: To determine the location of hubs in road passenger transportation plan, a method based on multi-objective optimization is presented in this paper. First, the road passenger transportation network in planning area is simplified as a directed graph and the hub location problem is transformed into 0-1 planning problem. Then the total hubs building cost, passenger network transportation expenses, and trip distance is selected as the optimization objectives, which is subject to the actual conditions of road passenger transportation. Finally, multi-objective genetic algorithm based on the selection after multi-objective value ordering and combining is adopted for model solution, and a computation example of passenger hub location is tested and analyzed.

Key words: traffic engineering, transportation hub location, multi-objective optimization, genetic algorithm

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