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基于改进的模拟退火遗传算法的公交线网优化
引用本文:满英,刘三阳,陈小娟. 基于改进的模拟退火遗传算法的公交线网优化[J]. 四川理工学院学报(自然科学版), 2008, 21(1): 1-3
作者姓名:满英  刘三阳  陈小娟
作者单位:西安电子科技大学理学院,西安,710071
摘    要:文章将遗传算法与改进的模拟退火算法相结合组成混合改进的模拟退火-遗传算法。研究了以居民乘车出行时间最短和公交部门投入最少为目标建立的公交线网优化的模型,并利用改进的模拟退火-遗传算法对该模型进行求解。通过温州滨海新区的规划实例研究验证方法的实用性。

关 键 词:公交线网  遗传算法  改进的模拟退火算法  混合算法
文章编号:1673-1549(2008)01-0001-03
收稿时间:2007-06-26
修稿时间:2007-06-26

Public Transit Network Optimization Based on Improved Simulated Annealing Genetic Algorithms
MAN Ying,LIU San-yang,CHEN Xiao-juan. Public Transit Network Optimization Based on Improved Simulated Annealing Genetic Algorithms[J]. Journal of Sichuan University of Science & Engineering(Natural Science Editton), 2008, 21(1): 1-3
Authors:MAN Ying  LIU San-yang  CHEN Xiao-juan
Abstract:Improved Simulated Annealing Algorithm and Genetic Algorithm is combined to become Hybrid Algorithms.Analyze transit network optimization model regarding the least travel time by bus and the lowest cost as objective function and use hybrid algorithms to solve this optimization model.Finally,an example of transit planning of Binhai new area in Wenzhou is given to verify the usability of the method.
Keywords:public transit network  genetic algorithm  improved simulated annealing algorithm  hybrid algorithm
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