基于粒子群优化算法的城市轨道客运定价双层规划模型研究  

Research on Particle Swarm Optimization Algorithm Based Bilevel Programming Model for Urban Rail Transit's Pricing

作　　者：彭亚美[1] 杨家其[1] 赵学彧[1] 

机构地区：[1]武汉理工大学交通学院,武汉430000

出　　处：《武汉理工大学学报（交通科学与工程版）》2016年第3期535-539,共5页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：吉林省交通科技项目资助(多种交通运输方式协同营运组织与管理;长吉图综合交通运输网评估及优化)

摘　　要：城市轨道交通是现代城市发展中重要的交通方式之一,其社会效益和经济效益都很重要,合理制定票价有利于城市轨道交通稳定发展.在各种公共交通公平竞争、满足乘客出行服务需求的前提下,找出城市轨道客运票价制定的最优策略,并建立了公共交通出行方式选择的Logit模型.同时兼顾城市公共交通运营公司和出行者各自的利益,采用粒子群优化算法构建了双层规划模型,并应用案例进行分析,分析了该模型的可行性和实用性.结果表明,采用该模型进行票价制定合理有效.As urban rail transit is one of the important transportation methods,the social and economic benefits of urban rail transit are both important.Therefore,a reasonable ticket price plays an important role for the stable development of urban rail transit.Under the conditions of impartial competition among several transportation models and meeting the demand of passengers＇ traveling service,the optimal strategy of ticket price formulation is determined and the Logit model for the selection of public transit methods is established in this paper.Meanwhile,considering the benefits of urban rail transit company and travelers respectively,this paper adopts the particle swarm optimization algorithm to establish the Bilevel programming model.The feasibility and utility of the established model are analyzed based on practical examples.The results demonstrate that the model is reasonable and effective in ticket pricing and helpful for the development of the urban rail transit.

关 键 词：城市轨道交通 票价制定 LOGIT模型 双层规划模型 粒子群优化算法 

分 类 号：U121[交通运输工程]