夜间不定车速环境下的优化调度模型分析  

Analysis of optimal scheduling model in variable speed environment at night

作　　者：崔永锋[1] 周丁丁[1] 

机构地区：[1]周口师范学院计算机科学与技术学院,河南周口466001

出　　处：《计算机工程与应用》2016年第9期239-242,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(No.U1204618);河南省信息技术教育研究规划项目(No.ITE12064);河南省科技攻关项目(No.162102310614)

摘　　要：在车辆调度的过程中,夜间环境下对车辆行驶状况的影响因素较多,车速不定,车辆调度的非线性将大大增加,传统的车辆调度模型应用到夜间环境下时,存在调度误差大,耗时严重的问题。提出基于模拟退火-遗传算法的夜间不定车速环境下的调度方法。利用模拟退火算法处理非线性问题的优势,结合遗传算法的优化求解功能,建立基于模拟退火-遗传算法的车辆优化调度模型,针对该模型求解,获取车辆调度的最优值,实现夜间不定车速环境下的优化调度。实验结果表明,利用GA-SA进行夜间不定车速环境下的优化调度,能够缩短调度时间,缓解车辆运行过程中的拥堵,极大提高了车辆运行速度,满足车辆调度的实际需求。In the process of vehicle scheduling, the travel condition of vehicles is influenced by more factors at night. If the speed is not certain, the non-linearity of vehicle scheduling is increasing greatly. When the traditional model of vehicle scheduling is applied at night, the problems of big schedule errors and costing time seriously happen. It puts forward a scheduling method based on the simulated annealing-genetic algorithm, and it is applied to the night. It takes advantage of the simulated annealing-genetic algorithm to deal with the nonlinear problems, and combines the solving optimization of simulated annealing algorithm to build the vehicle＇s optimized scheduling model. It gets the optimal value of vehicle scheduling, and realizes the optimal scheduling of variable speed at night. Experimental results show that taking advantage of GA-SA to optimize schedule variable speed at night can shorten the time of scheduling, and remit the congestion.It has greatly improved the running speed of cars and meets the actual demand of vehicle scheduling.

关 键 词：夜间 不定车速 车辆调度 遗传算法 模拟退火算法 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]