讲座题目：Modeling and Simulation Methods for Facility Location Problems with Disruptions
主 讲 人：Prof. XUEPING LI.
主 持 人：蹇明教授
Xueping Li is an Associate Professor of Industrial and Systems Engineering and the Director of the Ideation Laboratory (iLab) and co-Director of the Health Innovation Technology and Simulation (HITS) Lab at the University of Tennessee - Knoxville. He holds a Ph.D. from Arizona State University. His research areas include complex system modeling, simulation and optimization, information assurance, scheduling, supply chain management, data analytics, and health systems engineering. He is a member of IIE, IEEE, ASEE and INFORMS.
Research Interests and Expertise
?Complex systems modeling, simulation, and optimization
?Healthcare simulation & logistics modeling
?Scheduling, applied statistics, web mining, and Grid computing
?Supply Chain Management and Biomass Logistics
?Wireless Sensor Networks, Cyber Trust, and Anomaly Detection Systems
?Health Information Technology and Health Systems Engineering
?Quality of Service of computer and network systems and Information Systems Assurance, System Reliability
Fortifying facilities within a supply chain network can mitigate facility failures due to natural and/or human-caused disruptions. In this research, we study an r-interdiction median problem with fortification (RIMF) that simultaneously considers two types of disruption risks: random, or naturally-caused, facility failures and facility failures due to human-caused attacks such as cyber-attacks. The problem is to determine the allocation of limited facility fortification resources to an existing network. Firstly, we model the problem as a bi-level programming model that generalizes the r-interdiction median problem with probabilistic fortification. The lower level problem, i.e., the interdiction problem, is a challenging high-degree non-linear model. In the literature, only enumeration methods are applied to solve a special case of the problem. By exploring the special structural property of the problem, we propose an exact cutting plane method for the problem. For the high level fortification problem, an effective logic based Benders decomposition algorithm is proposed. Secondly, we build an agent-based simulation model to study RIMF. We develop a simulation model that analyzes disruption and fortification events in a manner resembling a repeated Stackelberg competition, where facility fortification decisions are made anticipating disruptions. The most important facilities - facilities which result in the largest incurred transportation cost if they were to fail/be disrupted - are fortified. Finally, computational studies are conducted.