The research in public transit scheduling based on the improved genetic simulated annealing algorithm

Chang-sheng Zhu, Hongmei Huang, Yuan Yuan, Qing-rong Wang
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引用次数: 2

Abstract

In this work,we set up public transit planning model by analysising of vehicle dispatching and taking both interest of bus company and passenger into consideration. using the improved genetic simulated annealing algorithm(the improved GA-SA) to carry out optimization for public transit dispatching model,and overcomes the problems such as evolution is slow,precocious, local optimal solution and so on, it can find the approximate optimum solution, reliably, from the huge search space of scheduling optimization problem. intelligent scheduling optimization problem in the great search space to find reliable optimal solution or approximate optimal solution. Finally,we use MATLAB to carry on simulation experiment. the results show that the improved GA-SA has higher efficiency than traditional GA.
基于改进遗传模拟退火算法的公共交通调度研究
本文通过对车辆调度的分析,同时考虑公交公司和乘客的利益,建立了公共交通规划模型。利用改进的遗传模拟退火算法(改进GA-SA)对公交调度模型进行优化,克服了进化缓慢、早熟、局部最优解等问题,能够从调度优化问题巨大的搜索空间中可靠地找到近似最优解。智能调度优化问题在大搜索空间中寻找可靠的最优解或近似最优解。最后,利用MATLAB进行仿真实验。结果表明,改进遗传算法比传统遗传算法具有更高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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