Image courtesy of Prof. Huseyin Topaloglu

Peter Jackson is currently conducting research in service parts supply chains, online “look-ahead” inventory policies, service-differentiated stocking policies, stocking policies for parts with highly correlated demands, and systems engineering approaches to designing real-time response systems for hospitals and first responders to deal with a mass casualty event.

Mark Lewis works on resource allocation questions involved in optimization of production processes. He has more recently also expanded his research to include areas of pricing used as a congestion control mechanism and basic inventory control. Inventory applications include classic single-commodity periodic review models and stochastic cash balance.

Jack Muckstadt addresses issues in a broad range of supply chain system contexts, ranging from homeland security issues through automotive environments.

Robin Roundy has general interests in supply chain management. His current research activities address forecasting, planning for uncertainty, capacity expansion, supply chain architecture, inventory management, auctions in supply chain settings, and financial risk in global supply chains.

Paat Rusmevichientong focuses on operational challenges faced by companies in the area of pricing, marketing, and supply chain management. He has worked with companies in e-commerce and automotive industries.

David Shmoys studies the design of algorithms for inventory models with the aim of devising new computational approaches for which one can prove strong worst-case bounds on their performance. This includes work on deterministic models such as the joint replenishment problem and its generalizations, and stochastic inventory models such as the multiperiod newsvendor problem. These theoretical investigations are complemented by empirical studies to extend the results into practical implementations for computing good solutions. The work on stochastic models is part of a larger research program to design provably good algorithms for intractable discrete stochastic optimization problems.

Huseyin Topaloglu is interested in applications of stochastic programming, simulation and approximate dynamic programming for large-scale resource allocation problems under uncertainty. The primary application area of his research is the operational vehicle allocation decisions in transportation systems. He is also interested in strategic decisions in transportation systems, such as pricing, fleet sizing, and capacity planning.