捆绑调教

报告题目：Online Demand Fulfillment and Network Design: From Complete Resource Pooling to Asymmetric Markets

报告时间：2026年11月24日（周二）上午10:00

报告地点：旭日楼308室

报告人：Dr. Zhen Xu

Abstract: This talk investigates online demand fulfillment in networks with limited flexibility, arbitrary resources, and diverse request types, where irrevocable fulfillment decisions must be made in real-time. Integrating network revenue management (NRM) with re-optimization techniques, we first establish a fundamental connection between the non-degeneracy of the deterministic linear program (DLP) and the complete resource pooling (CRP) condition. Under this framework, we demonstrate that a probabilistic fulfillment policy with a re-solving heuristic, alongside a load deviation policy, can achieve a uniformly constant performance bound independent of the time horizon and resource capacities.

We then extend this analysis to highly asymmetric markets, where massive disparities in market shares render traditional performance metrics, such as the generalized chaining gap (GCG), less effective. To address this, we introduce a novel network condition termed -connectivity and prove it is both necessary and sufficient for maintaining bounded performance in asymmetric environments. Crucially, our findings reveal that classic structures like the 'long chain' may fail when low-demand markets are dispersed. Instead, we propose a 'hub-and-spoke' configuration embedded with a shorter long chain as an optimal network design strategy to mitigate -disconnectivity and ensure robust system performance.

Bio: Zhen Xu is currently a Lecturer in the Management School at the University of Liverpool. His research lies at the interface of operations research, applied probability, and machine learning, with a focus on stochastic process control, dynamic programming, and data-driven decision making for a variety of static and dynamic models. His research has been published in leading academic journals, including Management Science, Manufacturing & Service Operations Management (MSOM), Production and Operations Management (POM), and Mathematics of Operations Research.