Online Demand Fulfilment and Network Design: From Complete Resource Pooling to Asymmetric Markets, a seminar by Dr Zhen Xu (University of Liverpool)

Online Demand Fulfilment and Network Design: From Complete Resource Pooling to Asymmetric Markets

By Dr Zhen Xu from the University of Liverpool

Abstract

This talk investigates online demand fulfilment in networks with limited flexibility, arbitrary resources, and diverse request types, where irrevocable fulfilment 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 fulfilment 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.

About the speaker

Zhen Xu is currently working as a Lecturer in Management School, University of Liverpool. His research interest lies at the interface of operations research, applied probability, and machine learning, with a focus on stochastic process control, dynamic programming, supply chain management, 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 and Mathematics of Operations Research.