摘要
传统民航路径的选择主要依靠人工方法来进行,其不仅存在较强的主观性、容易出错,还会增加额外的成本。针对上述缺点,建立了一种带时间窗的民航运输路径模型。同时将模拟退火算法与遗传算法相结合,使模型兼具局部求解与全局求解的能力。在对算法进行改进的层面上,使用混沌公式初始化种群,并利用自适应函数来实时优化交叉算子及变异算子,进而有效提高了算法的收敛速度及求解准确度。实验结果表明,采用所提算法优化得到的班机数量准确度与实际值最为接近。且迭代结果也证明了该算法的局部和全局求解能力均较为出色,故可应用于实际民航运输路径的优化问题中。
The traditional civil aviation route selection method mainly depends on manual work,which not only has strong subjectivity and is easy to make mistakes,but also will increase additional costs.In view of the above shortcomings,this paper establishes a civil aviation transportation path model with time window,and combines simulated annealing algorithm with genetic algorithm to make the algorithm have the ability of local solution and global solution.In this paper,the convergence speed and mutation formula of the chaos operator are improved in real⁃time,and then the convergence speed and mutation function of the chaos operator are improved in real⁃time.The experimental results show that the accuracy of the number of flights optimized by the algorithm proposed in this paper is the closest to the actual value.The iterative results also prove that the local and global solution ability of the algorithm is excellent,and can be used in the optimization of the actual civil aviation transportation route.
作者
王珺
WANG Jun(Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China)
出处
《电子设计工程》
2023年第20期77-81,共5页
Electronic Design Engineering
基金
陕西省教育科学“十三五”规划2017年度课题(SGH17V012)。
关键词
模拟退火算法
遗传算法
路径优化
局部求解
民航运输
simulated annealing algorithm
genetic algorithm
route optimization
local solution
civil aviation transportation
