Equity-Driven Facility Location: A Two-Stage Robust Optimization Approach
IRB 3137 or Zoom: https://umd.zoom.us/j/6778156199?pwd=NkJKZG1Ib2Jxbmd5ZzNrVVlNMm91QT09
Thursday, March 14, 2024, 3:30-4:30 pm 
Abstract
In the first part of the talk, we discuss the computational challenge of incorporating equity in p-median facility location models under uncertain demand and discuss how two-stage robust programming can be employed to address the challenge. Our research evaluates various equity measures appropriate for facility location modeling and proposes a novel approach to reformulating the problem into a two-stage robust optimization framework, enhancing computational efficiency caused by incorporating equity and uncertainty into these models. We provide two solution algorithms: an exact and an inexact column-and-constraint generation (C\&CG) method. Our findings show that when dealing with a small number of variables, inexact C\&CG can improve the performance of exact C\&CG for our problem. We further conduct a detailed evaluation of the tractability of our reformulated model and the effectiveness of various equity measures through a real-world case study of Metro Vancouver.
In the second part of the talk, I briefly review our previous works on robust kidney exchange for further collaboration opportunities.
Bio
Hoda Bidkhori is currently an assistant professor in the Department of Computational and Data Sciences at George Mason University. Her research focuses on the theory and applications of data analytics and data-driven decision-making; the application areas include logistics, supply chain management, and healthcare. Before, she was an assistant professor at the University of Pittsburgh. She also obtained her Ph.D. in Applied Mathematics from MIT.
This talk is organized by Kishen N Gowda