中断离港航班恢复的改进NSGA2算法  

Improved NSGA2 algorithm for disrupted departure flights recovery

作　　者：陈可嘉 吴钧涛 CHEN Kejia;WU Juntao(School of Economics and Management,Fuzhou University,Fuzhou 350108,China)

机构地区：[1]福州大学经济与管理学院,福州350108

出　　处：《北京航空航天大学学报》2024年第6期1784-1793,共10页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国家社会科学基金(18BGL003)。

摘　　要：为解决因突发事件产生的航空公司航班中断问题,对中断的离港航班进行恢复,构建最小化航空公司总延误成本和最小化乘客总延误时间的双目标优化模型,设计基于支配强度的自适应非支配排序遗传算法(ANSGA2-DS)。提出3种改进操作:快速支配排序方法、新的拥挤距离和自适应精英保留策略。通过福州长乐国际机场某航空公司的运行数据对所提算法进行验证,实验结果表明:与传统的先规划先服务方法相比,所提算法得到的解有大幅优化;与ε约束法相比,所提算法的求解时间总体上低于ε约束法,且求解结果接近ε约束法所得最优结果;与NSGA2、MOEAD等多目标优化算法相比,所提算法表现出更优的性能,能够有效且高效地解决问题,为航空公司达成优化的解决方案提供基础。To solve the problem of airline flight disruption caused by emergencies,this paper recovers the disrupted departure flight.A bi-objective optimization model for minimizing airline delay cost and passenger delay time is constructed.An adaptive non-dominated sorting genetic algorithm-Ⅱbased on dominant strengths(ANSGA2-DS)is designed.The novel crowding distance,the adaptive elitist retention technique,and the quick dominant sorting approach are the three enhanced operations that are given.The proposed algorithm is verified by the operation data of an airline in Fuzhou Changle International Airport.The experimental results reveal that,compared with the traditional first scheduling first serve method,the algorithm proposed in this paper can reduce the costs greatly.In contrast to theε-constraint approach,theε-constrained approach requires a longer solution time,and the resulting solution results are similar to those of theε-constrained approach.Compared with the NSAG2 algorithm and the MOEAD algorithm,the algorithm proposed in this paper shows better performance.The proposed algorithm can solve the problem effectively and efficiently,and provide a basis for airlines to reach an optimized solution.

关 键 词：航空运输 中断航班恢复 多目标遗传算法 离港航班 双目标优化 

分 类 号：V355[航空宇航科学与技术—人机与环境工程]