首页 | 本学科首页   官方微博 | 高级检索  
     

基于遗传算法的通道上停车换乘量确定方法
引用本文:陈群,姚加林,晏克非.基于遗传算法的通道上停车换乘量确定方法[J].计算机工程,2008,34(4):201-202.
作者姓名:陈群  姚加林  晏克非
作者单位:1. 中南大学交通运输工程学院,长沙,410075
2. 同济大学交通运输工程学院,上海,200092
基金项目:中南大学博士后科研基金资助项目;上海市科委基金资助项目(04dz05808)
摘    要:根据外来客流进入城市中心的出行过程与机理,最小化所有客流出行(自城市外围到达市中心区域)的出行费用(私人车辆行驶时间与公交行驶时间总行程时间、换乘时间、停车费用等),建立、确定了各停车换乘点(P+R)处合理换乘量的双层规划模型,为各P+R的停车换乘诱导提供了依据,并给出模型的遗传算法求解方法。仿真示例证明了该方法的有效性。

关 键 词:停车换乘  双层模型  换乘量  遗传算法
文章编号:1000-3428(2008)04-0201-02
收稿时间:2007-04-01
修稿时间: 

Method for Determining Park & Ride Sites' Transfer Volume on Passage Based on Genetic Algorithm
CHEN Qun,YAO Jia-lin,YAN Ke-fei.Method for Determining Park & Ride Sites' Transfer Volume on Passage Based on Genetic Algorithm[J].Computer Engineering,2008,34(4):201-202.
Authors:CHEN Qun  YAO Jia-lin  YAN Ke-fei
Affiliation:(1. School of Transport Engineering, Central South University, Changsha 410075; 2. School of Transport Engineering, Tongji Uniersity, Shanghai 200092)
Abstract:After analyzing trip process from out of city to downtown, and for minimizing the total travel expenses(car travel time and public transportation travel time, transfer time, parking fee, etc.) of all traffic trips(from out of city to downtown city), the bi-level programming model is established to determine park &; ride sites’ transfer volume, which offers foundation for parking guidance on the passage. The solution method using genetic algorithm of the model is presented, and a simulation case shows the method is effective.
Keywords:Park&Ride(P+R)  bi-level programming model  transfer volume  genetic algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机工程》浏览原始摘要信息
点击此处可从《计算机工程》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号