遗传-牛顿算法在公交智能调度中的应用  

Application of Genetic-Newton Algorithm in Public Transport Dispatching

作　　者：张晓培[1] 李茂军[1] 

机构地区：[1]长沙理工大学电气与信息工程学院,湖南长沙410114

出　　处：《计算机测量与控制》2010年第12期2830-2832,共3页Computer Measurement &Control

基　　金：国家自然科学基金(50775015)

摘　　要：针对公交公司需要解决的典型问题公交车辆的优化调度,提出了一种遗传算法与牛顿算法相结合的智能优化算法;并用该混合算法对调度模型进行优化;首先在兼顾公交公司与乘客双方利益的情况下,建立了以发车间隔时间为决策变量的公交车优化调度模型,再利用遗传算法对决策变量进行优化,然后用牛顿法对其优化的结果进行深一步的搜索,使其优化结果精度提高;仿真结果表明,该混合算法比标准的遗传算法更有效地提高公交车辆运营效率并降低其费用成本。Optimal schedule of public transport is a typical issue that needs to be taken into consideration by public transport company.An intelligent optimization algorithm which were combined by Genetic Algorithm and Newton,and using this hybrid algorithm to optimize the scheduling model.Firstly,balancing the interests of public transport company and passengers,the optimal schedule model of public transport was set up with the departure interval as the variable and was optimized by Genetic Algorithm,then using Newton to optimize the results of its further,in order to improve the accuracy of optimization results.The simulation results indicate that this hybrid algorithm has the higher efficiency than simple Genetic Algorithm;it can improve the operational efficiency of public transport and reduce the costs.

关 键 词：公交车 调度 发车间隔 遗传算法 牛顿法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]