TIME & LOCATION
April 11, 2025, 10:00-11:00
Room 1521, Building of Humanities
TENCENT MEETING ROOM: 898-169-685
TOPIC
In this presentation, we explore the application of stochastic modeling techniques to address complex, real world decision-making challenges. We focus on two-stage stochastic programming and stochastic sequential modeling using Markov Decision Processes (MDPs). Through practical examples, including omnichannel retailing, staff scheduling in manufacturing, and hospital operating room scheduling, we illustrate how uncertainty can be effectively managed with advanced solution methodologies, such as Benders decomposition and reinforcement learning. The insights gained from these approaches offer valuable perspectives on operational efficiency, resource allocation, and cost management in uncertain environments. This talk will provide attendees with a deeper understanding of how to apply stochastic models to solve real-life problems and drive data-informed decision-making.
ABOUT THE LECTURER
Lele (Joyce) Zhang is Associate Professor at the School of Mathematics and Statistics, The University of Melbourne (UoM). She has a Bachelor's Degree in Engineering (Southeast University, China), and a PhD in Operations Research (UoM). Her areas of expertise are mathematical modelling and optimisation, Operations Research, City Logistics, traffic flow theory, Monte Carlo simulation, scheduling theory, and time series analysis. She is a Chief Investigator of ARC Training Centre in Optimisation Technologies, Integrated Methodologies, and Applications (OPTIMA), Chief Investigator of multiple Australia Research Council Discovery Projects and Associated Investigator of ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). Lele is a co-founder of Physical Internet Lab at UoM and has research close collaborations with a number of industries in logistics, transport and healthcare.