TITLE: Reliable Facility Location under Probabilistic Disruptions

SPEAKER: Professor Yanfeng Ouyang

ABSTRACT:

While planning facility locations in a supply chain to serve spatially distributed customers, we consider the case where facilities are subject to probabilistic failure (due to reasons such as natural or man-made disasters). If a facility fails, customers may have to be reassigned to
other facilities and incur excessive transportation cost.

Mathematical models are developed to determine optimal facility locations as well as customer assignment strategies, allowing facilities to fail under location-dependent probabilities. The goal is to minimize the sum of initial facility construction costs and expected customer transportation costs under normal and failure scenarios. This talk will focus on a continuum approximation (CA) model that accurately predicts the total logistics cost for large-scale systems. This model not only serves as a very efficient heuristic method to find near-optimum discrete solutions, but also helps provide useful managerial insights (i.e., solution robustness to input data errors, and advantage of having diversity in design parameters).

We also develop a discrete mixed-integer program (MIP) model and a customized Lagrangian relaxation algorithm. Extensive numerical experiments are conducted for both the discrete model and the continuous model. It is shown that the CA model provides a very good alternative especially for large-scale problem instances, when the MIP model has difficulty solving them in a reasonable amount of time.

Bio

Yanfeng Ouyang received his Ph.D. in civil engineering from the University of California at Berkeley in 2005. Since then, he has been on the faculty of the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). He currently serves on the editorial advisory board for the journal Transportation Research Part B, and is a member of the Transportation Research Board's Network Modeling Committee (ADB30). His research interests focus primarily on improving stability and efficiency of transportation, logistics, and supply chain systems.

Dr. Ouyang received the "Faculty Early Career Development (CAREER) Award" from the National Science Foundation in April 2008. He has been on UIUC's "List of Teachers Ranked as Excellent by Their Students" four times. While a student at Berkeley, he received the Gordon F. Newell Award in 2005, and the "Outstanding Graduate Student Instructor Award" in 2004.