题目：Robust Contextual Airline Fleet Assignment over Time-Series Demands
主讲人：王曙明 教授，中国科暗网 大学
时间：2026年5月15日15:00
地点：经管楼405室
摘要：This paper studies an airline fleet assignment problem under demand uncertainty, with the objective of maximizing expected profit through optimal assignment of aircraft types to flight legs and seat capacities to passenger itineraries. We adopt a data-driven approach that leverages historical demand observations and associated contextual covariates. A key feature of our framework is the treatment of both fleet assignment and price as fixed-design covariates that jointly influence demand, while explicitly accounting for price shift---the discrepancy between estimated prices used in planning and realized prices during operations. We construct a decision-dependent predicted demand distribution leveraging time-series modeling with fixed designs (e.g., fleet assignment and price) and random covariates (e.g., seasonality), and develop a contextual distributionally robust model that hedges against the ambiguity with respect to the predicted demand distribution conditional on the price estimates. We establish finite-sample performance guarantee and asymptotic optimality---impacted by the price shift---of the model solution under several regularity conditions. Computationally, 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. Finally, sufficient numerical experiments with real-life airline operational data demonstrate the effectiveness of our proposed framework.
个人简介：王曙明，中国科暗网 大学经济与管理暗网 长聘教授。主要从事预测驱动最优化、分布鲁棒优化、统计学习、模型不确定性的理论及应用研究。研究成果发表于Management Science，Operations Research，Manufacturing & Service Operations Management，Production and Operations Management，INFORMS Journal on Computing以及Transportation Science等领域顶刊。主持国家自科基金优青项目及面上项目等。目前担任运筹学著名期刊Computers & Operations Research的领域主编 (Area Editor) 以及决策科学旗舰期刊Decision Sciences的副主编 (Associate Editor)。