Scholarlink

<p>Flight rescheduling problems have received considerable attention in recent decades, but most studies have neglected the role of airline decision-making and passenger satisfaction, which greatly affects airline competitiveness. In this paper, an airline-driven arrival flight rescheduling problem considering passenger satisfaction is investigated when a ground delay program (GDP) is issued. An improved NSGA-II (iNSGA-II) is tailored to solve the proposed bi-objective model, aiming to minimize the total relevant cost and maximize passenger satisfaction, where passenger satisfaction is portrayed using Prospect Theory. As the model considers multiple recovery strategies, a chromosome coding method is designed, and population initialization, crossover, and mutation are tailored to match the problem characteristics. Additionally, the de-duplication strategy, probability selection, and perturbation strategy are introduced to enhance the algorithm’s developmental capabilities. The external archive is also implemented to maintain population diversity. The optimal key parameters used in iNSGA-II are obtained by the Taguchi method. The experimental results prove that the solution of iNSGA-II outperforms the traditional first-come-first-served (FCFS) and can find a reasonable solution set close to the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\epsilon \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>ϵ</mi> </math></EquationSource> </InlineEquation>-constraint method in less time. Meanwhile, it is verified that iNSGA-II has better performance and is more conducive to finding the global better Pareto fronts by comparing with NSGA-II, MOEA/D, and MOPSO, which can better provide the basis for the airline’s preference decision. Finally, management insights are given by analyzing solutions and the distribution of objective values. The research can offer theoretical insights and practical guidance to assist airlines in rescheduling flights.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Airline-Driven Arrival Flight Rescheduling Problem Considering Passenger Satisfaction Using Improved NSGA-II

  • 期刊论文

  • 发表日期：

    2025年7月10日

查看全文
  • Kejia Chen,
  • Hongjun Wang

摘要

Flight rescheduling problems have received considerable attention in recent decades, but most studies have neglected the role of airline decision-making and passenger satisfaction, which greatly affects airline competitiveness. In this paper, an airline-driven arrival flight rescheduling problem considering passenger satisfaction is investigated when a ground delay program (GDP) is issued. An improved NSGA-II (iNSGA-II) is tailored to solve the proposed bi-objective model, aiming to minimize the total relevant cost and maximize passenger satisfaction, where passenger satisfaction is portrayed using Prospect Theory. As the model considers multiple recovery strategies, a chromosome coding method is designed, and population initialization, crossover, and mutation are tailored to match the problem characteristics. Additionally, the de-duplication strategy, probability selection, and perturbation strategy are introduced to enhance the algorithm’s developmental capabilities. The external archive is also implemented to maintain population diversity. The optimal key parameters used in iNSGA-II are obtained by the Taguchi method. The experimental results prove that the solution of iNSGA-II outperforms the traditional first-come-first-served (FCFS) and can find a reasonable solution set close to the \(\epsilon \) ϵ -constraint method in less time. Meanwhile, it is verified that iNSGA-II has better performance and is more conducive to finding the global better Pareto fronts by comparing with NSGA-II, MOEA/D, and MOPSO, which can better provide the basis for the airline’s preference decision. Finally, management insights are given by analyzing solutions and the distribution of objective values. The research can offer theoretical insights and practical guidance to assist airlines in rescheduling flights.