Flight scheduling and fleet assignment are important steps of an airline planning process. In light of the reciprocal relationship between air transport supply and demand, a key element of these models is to devise effective methods to both incorporating estimation of total market demand and allocating passengers over the available itineraries in a specific market. In this paper, we present a novel mixed integer nonlinear flight scheduling and fleet assignment optimization model wherein air travel demand generation and allocation are simultaneously and consistently endogenized. Using a nested logit formulation, we jointly model competition among air travel itineraries and appraise the contribution of specific itinerary attributes to demand generation, therefore yielding a more comprehensive and explicit representation of supply-demand interactions. Computational testing based on realistic problem instances reveals that the model can optimize mid-size hub-and-spoke networks within reasonable time. Further analyses illustrate the benefits that can be derived from the application of the proposed approach using real-world data for a major European airline. Results demonstrate that the proposed approach can significantly enhance operating profits by up to 6.9% and better reveal opportunities for demand stimulation against a conventional approach using inelastic trip generation.

排班和机队分配是航空公司计划过程中的重要步骤。鉴于航空运输供需之间的相互关系，这些模型的关键要素是设计有效的方法，既可以纳入对总市场需求的估算，也可以在特定市场的可用行程中分配旅客。在本文中，我们提出了一种新颖的混合整数非线性飞行计划和机队分配优化模型，其中航空旅行需求的生成和分配被同时且一致地内生。使用嵌套的logit公式，我们共同模拟了航空行程之间的竞争，并评估了特定行程属性对需求产生的贡献，因此产生了供需交互的更全面，更明确的表示。基于实际问题实例的计算测试表明，该模型可以在合理的时间内优化中型轮辐网络。进一步的分析表明，使用欧洲一家主要航空公司的实际数据，可以从建议的方法的应用中获得收益。结果表明，与使用无弹性行程生成的传统方法相比，该方法可以显着提高营业利润高达6.9％，并更好地揭示刺激需求的机会。