改进遗传算法的公交线网优化研究  

Research on Bus Network Optimization Based on Improved Genetic Algorithm

作　　者：韩天齐 宋波 HAN Tianqi;SONG Bo(School of Cybersecurity,Chengdu University of Information Technology,Chengdu,Sichnan 610225,China)

机构地区：[1]成都信息工程大学网络空间安全学院,四川成都610225

出　　处：《微型电脑应用》2020年第4期88-90,共3页Microcomputer Applications

摘　　要：公交是一种主要的城市公共交通工具,针对现有城市公交线网设计时普遍存在缺乏层次性规划的问题,提出了改进遗传算法的公交线网优化方法。首先对当前城市公交线网优化的研究现状进行分析,然后设计相应的城市公交线网优化数学模型,采用改进遗传算法对城市公交线网优化数学模型进行求解,并通过引入动态惩罚系数确定适应度,以调整收敛速度;通过自适应机制确定交叉概率和变异概率,以调整搜索空间。最后采用具体算例对本文方法的性能进行分析。结果表明,这个方法不仅可以找到更优的城市公交线网优化方案,而且求解的效率得到了明显提升。Bus is a major urban public transport. Aiming at the problem of lacking hierarchical planning in the design of urban public transport network, this paper proposes an improved genetic algorithm for the optimization of urban public transport network. Firstly, the current research situation of urban public transport network optimization is analyzed, the corresponding mathematical model of urban public transport network optimization is designed, and then an improved genetic algorithm is used to optimize the mathematical model of urban public transport network optimization. Finally, the performance of the proposed method is analyzed by a specific example. The results show that the proposed method can find a better urban public transport network optimization scheme, and efficiency of solution has been improved obviously.

关 键 词：城市公交线网 层次性规划 遗传算法 收敛速度 数学模型 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]