物流工程学院专家讲座：情境驱动的鲁棒机队分配

报告时间：2025年7月3日（周四），10:00-11:30

报告地点：物流楼508

主 讲 人: 张真真

报告摘要：

We study an airline fleet assignment problem under demand uncertainty, where the airline aims to maximize its expected total profit by determining the aircraft type assigned to each flight leg and the seat capacity reserved for each itinerary. We consider a data-driven setting that leverages historical observations of demand and the associated contextual information or covariates, where the fleet assignment decision and price information serve as key covariates affecting the underlying demand. Also, the price estimates employed in the planning stage can be different from the price realizations in the operational stage, leading to a phenomenon of price shift. We construct a decision-dependent predicted demand distribution leveraging a demand prediction model of multivariate regression with fixed designs (e.g., fleet assignment and price) and random covariates (e.g., seasonality), and develop a contextual distributionally robust model regularized with Wasserstein distance that hedges against the distributional ambiguity induced by the predicted demand distribution. We establish finite-sample performance guarantee and asymptotic optimality, impacted by the price shift, of the model solution, under several regularity conditions. We also analytically measure the value of decision dependency via analyzing the performance gap induced by the decision-omitted bias in the predictive modeling. Computationally, leveraging a reformulation of the contextual robust model, we show the proposed contextual robust airline fleet assignment model can be transformed into a mixed-integer linear program, without inducing additional integers to the assignment decisions. In addition, we also extend the model to hedge against the ambiguity on the price shift using ϕ-divergence. Extensive numerical experiments with real-life airline fleet operational data demonstrate the effectiveness of our proposed framework.

主讲人简介：

张真真，同济大学经济与管理学院长聘副教授、博士生导师。入选上海市高层次人才计划。长期致力于大规模整数规划和不确定优化的理论研究与算法设计，及在物流与运输规划、智能制造等方面的应用。目前已发表高质量论文30余篇，包括Operations Research、INFORMS Journal on Computing、Transportation Science、Transportation Research Part B、NeurIPS等，主持国家自然科学基金青年项目及优秀青年项目、上海市人才项目和华为、中远海运科研课题各1项，作为项目骨干参与创新研究群体和重点项目各1项。现任管理科学与工程学会交通运输分会执行秘书长、世界交通大会货运与物流系统优化技术委员会委员、运筹学会随机服务与运作管理分会理事，并长期担任Operations Research，Transportation Science等30多个国际知名期刊的审稿人。

来源：集装箱供应链技术教育部工程研究中心