ISE PhD Student
University of Tennessee
Friday, February 24, 2017 2:30-3:00pm
When designing a supply chain network, one of the most crucial decisions is to locate facilities. Considering facility disruption risks during the design phase helps to construct a supply chain network that effectively balances the efficiency and robustness. The reliable facility location problem extends the classical uncapacitated facility location problem by considering random facility disruptions. In this talk, we present a cutting plane algorithm that solves the reliable facility location problem with a general disruption distribution, i.e., heterogeneous failure rates and correlated failures. In addition, a distributionally robust stochastic programming model along with a hybrid cutting plane – column generation algorithm is presented. The computational results show that the cutting plane algorithm not only outperforms the best known algorithm in the literature that solves uncorrelated disruptions, but also efficiently solves moderate sized problem with correlated disruptions.
Kaike Zhang is a PhD student in the Department of Industrial & Systems Engineering at the University of Tennessee. Prior to his studies at UTK, he was a research assistant at Institute of Process Engineering, Chinese Academy of Sciences. He received his B.S. in Information Systems Management from Southeast University, China in 2012. Kaike’s research interests include logistics and supply chain management, computational integer programming.