基于定量分析的公交线路网络优化与粒子群算法

Particle Swarm Algorithm for Optimization of Urban Transport Network Based on Quantitative Analysis

针对公交线网优化问题,利用粒子群算法进行了研究。在考虑城市公交系统多因素的基础上,给出了公交线网的优化原则、优化目标和约束条件,并将优化目标和约束条件定量化处理,给出了相应的数学表达式。在定义6维空间的基础上,利用经济转化系数,将公交线网优化的多目标问题转化为单目标优化问题的情况下,建立了公交线网优化的线性模型,并用粒子群算法进行了求解计算。通过粒子在解空间中搜索,找到最佳的公交线路网络。最后对算法进行了实际应用分析,结果表明该法简单实用、结果可信,有广泛的应用前景,而且该法也为多目标优化问题提供了一种合理可行的方法。

A new method of public traffic line network optimization is presented by particle swarm algorithm. On the basis of considering each factor of urban public traffic line network, urban transport network optimization principle, optimum objects and corresponding constraints are presented. Mathematical expression for optimum objects and corresponding constraints are presented. Based on six dimensional space, a linear model of public traffic line network optimization is established by economical transformation coefficient. Then, particle swarm optimization algorithm is used to plan the public transport network. This method is simple and practical, and the result is believable and applicable as another reasonable and effective method for the multiple objective optimization.