基于改进的状态空间模型进化算法的航班优化调度  

Flight Optimized Scheduling of Modified State Space Model Evolutionary Algorithm

作　　者：李恒 王嘉[1] LI Heng;WANG Jia(Changsha Aeronautical Vocational and Technical College,Changsha Hunan 410124)

机构地区：[1]长沙航空职业技术学院,湖南长沙410124

出　　处：《长沙航空职业技术学院学报》2023年第4期11-17,共7页Journal of Changsha Aeronautical Vocational and Technical College

基　　金：长沙航空职业技术学院院级课题“面向多跑道的航班进离场协同调度研究”(编号:YC2205)阶段性研究成果。

摘　　要：单跑道进离港航班优化调度是将某一时间窗内进离港航班看作一个整体,对进离港航班进行统一优化排序,属于典型的组合优化问题。改进的状态空间模型序号编码进化算法(MOSEA)采用序号编码,不使用交叉算子,且通过构造状态进化矩阵来实现基因换位等遗传算子功能,使种群不断地进化,并结合选种池的选择操作实现种群的优胜劣汰。MOSEA算法将问题的解答过程表示为离散状态空间模型的动力学过程,突破了遗传算法的计算模式,简化了遗传操作,并研究了其在航班进离港优化调度中的应用。仿真实验表明:MOSEA算法与遗传算法、先到先服务(FCFS)航班排序相比,航班总延误时间分别降低了22.13%、32.06%,且运算速度更快。The optimization scheduling of single-runway arrival and departure flights is to take the approach and departure flights within a certain time window as a whole and make a unified optimization ranking of approach and departure flights,which is a typical combination optimization problem.This paper puts forward a Modified State Space Serial Number Coding Evolutionary Algorithm(MOSEA),and this algorithm adopts the serial number coding,do not use cross operators,and constructs a state evolution matrix to implement genetic operator transposition functions such as gene transposition,enabling the population to continuously evolve,and combining with the selection of seed pool operation to realize the evolution of the population.The MOSEA algorithm represents the process of solving questions as the dynamic process of the discrete state space model,breaks through the calculation mode of the genetic algorithm,simplifies the genetic operation,and studies its application in the optimal scheduling of flight arrival and departure ports.Simulation experiments show that compared with genetic algorithm and first come,first service(FCFS)flight ranking,the total flight delay time is reduced by 22.13%and 32.06%respectively,and the calculation speed is faster.

关 键 词：航班优化调度 状态空间模型进化算法 序号编码 延误时间 单跑道 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]