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粒子群优化算法在公交车智能调度中的应用
引用本文:付阿利,雷秀娟.粒子群优化算法在公交车智能调度中的应用[J].计算机工程与应用,2008,44(15):239-241.
作者姓名:付阿利  雷秀娟
作者单位:1.陕西师范大学 计算机科学学院,西安 710062 2.西北工业大学 自动化学院,西安 710072
基金项目:教育部科学技术研究重点项目
摘    要:运营车辆的智能排班是公交车辆智能调度需要解决的问题之一,关系到公交企业的经济效益与社会效益。采用兼顾公交公司与乘客双方利益的公交车辆调度模型,将带收缩因子和线性递减惯性权重的粒子群优化算法(W-K-PSO)应用到公交智能排班中。实例仿真结果表明该算法具有比其它优化算法更好的效率,是解决公交车智能调度问题的一个有效方法。

关 键 词:公交车调度  粒子群优化  线性递减惯性权重  收缩因子  
文章编号:1002-8331(2008)15-0239-03
收稿时间:2007-9-6
修稿时间:2007年9月6日

Intelligent dispatching of public transit vehicles using particle swarm optimization algorithm
FU A-li,LEI Xiu-juan.Intelligent dispatching of public transit vehicles using particle swarm optimization algorithm[J].Computer Engineering and Applications,2008,44(15):239-241.
Authors:FU A-li  LEI Xiu-juan
Affiliation:1.College of Computer Science,Shaanxi Normal University,Xi’an 710062,China 2.College of Automation,Northwestern Polytechnical University,Xi’an 710072,China
Abstract:The intelligent schedule of vehicles operation is one of the problems which need to be solved in the public transportation intelligent dispatch,it relates to the economic efficiency and social benefits of transit agency.The authors use a transit vehicle scheduling model which balancing between the interests of bus companies and passengers.The particle swarm optimization algorithm with constriction factor and linear descend inertia weight,namely W-K-PSO is applied to the intelligent schedule of vehicles operation.The simulation results show that W-K-PSO has the higher efficiency than other optimization algorithm and is one effective way optimizing the public transit vehicle dispatching.
Keywords:public transit vehicle dispatching  Particle Swarm Optimization(PSO)  linear descend inertia weight  constriction factor
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