演讲人: Prof. Weijun Xie，City University of Hong Kong

时间: 2026年10月16日10：00

地点: 同济大厦A楼306教室

讲座摘要: This paper resolves an open problem posed in the literature by proving that, in dual-sourcing inventory systems, the optimality gap of tailored base-surge (TBS) policies decays exponentially with the regular source lead time, with the express-source lead time fixed. In contrast to the existing approach, which relies on conditional Jensen inequalities and a vanishing-discount argument to establish asymptotic optimality, we develop a fundamentally different primal-dual framework. On the primal side, we derive a characterization of the optimal TBS policy using convexity and first-order optimality conditions in the TBS parameters $(r,S)$, which we then use to reformulate the TBS objective as a pricing-type representation. On the dual side, we develop infinite-horizon dual formulations for both closed-loop and semi-open-loop problems. A key technical step is verifying a transversality condition to show weak duality for the closed-loop formulations. We then construct an explicit dual solution for the semi-open-loop problem and show that its dual objective matches the best TBS objective. Finally, we perturb this dual solution to obtain a feasible dual solution for the closed-loop problem; the induced loss in the dual objective gives an explicit upper bound on the TBS optimality gap. By connecting this loss to a GI/GI/1 queue and exploiting its geometric mixing property, we prove the desired exponential decay. This significantly strengthens the state-of-the-art asymptotic-optimality result, which yields only a square root convergence rate. This paper has been finalists of 2026 INFORMS MSOM Best Paper Competition and 2026 INFORMS Geroge Nicholson Paper Competition.

演讲嘉宾简介: Dr. Weijun Xie is a Professor in the Department of Data Science at City University of Hong Kong. His research interests are theory and applications of stochastic, discrete, and convex optimization. His work has received multiple awards, including the 2025 INFORMS Computing Prize (Honorable Mention), the 2022 New Investigator Award from the Virginia Space Grant Consortium (NASA), the 2021 NSF CAREER Award, and the 2020 INFORMS Young Researchers Paper Prize. He currently serves as Associate Editor of Operations Research, Mathematical Programming, Manufacturing & Service Operations Management, Journal of Global Optimization, and Naval Research Logistics.