Dynamic stochastic matching problems arise in a variety of recent applications, ranging from ridesharing and online video games to kidney exchange. Such problems are naturally formulated as Markov ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

Efficiently operating a single microgrid (MG) is increasingly challenging due to volatile electricity demand and intermittent renewable generation. Traditional static networks often fail to adapt to ...

Dan Zhang is Associate Professor of Operations Management at Leeds School of Business, University of Colorado Boulder. Dr. Zhang teaches in the area of operations management and data analytics in ...

Water resource systems face uncertainties from climate variability, demand fluctuations and policy shifts. Stochastic optimisation offers mathematical frameworks to plan reservoir operations, ...