Friday, August 25, 2017 at 3:30pm
Inventory models encompass problems in stochastic control which arise in the optimization of supply chains and logistics networks and are of considerable interest to large companies, such as Amazon and Walmart. Many classical inventory models become notoriously challenging to optimize in the presence of positive lead times, since the state-space blows up and dynamic programming techniques become intractable. In this talk, we present a new algorithmic approach to such problems, which shows that as the lead time grows large, simple heuristics become asymptotically optimal. These results are quite surprising, as this setting had remained an open algorithmic challenge for over forty years. Our results provide a new algorithmic approach to these problems, as well as a solid theoretical foundation for the good performance of these heuristics observed numerically by previous researchers. Our approach combines ideas from the theory of random walks and convexity. The talk will be entirely self-contained, not requiring any specific background in the mathematics of inventories or operations research.
David A. Goldberg is an Associate Professor in Cornell's ORIE department. Previously, he was the A. Russell Chandler III Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his Ph.D. in Operations Research at MIT in 2011, and his B.S. in Computer Science (minors in Operations Research and Applied Math) from Columbia University in 2006. Goldberg’s research is in applied probability, on topics including inventory and queueing models, combinatorial optimization, robust optimization, and multi-arm bandits. His work has been recognized with accolades including an NSF CAREER award, 2015 Nicholson Competition first place, 2015 JFIG Competition second place, and 2014 MSOM and 2010 Nicholson Competitions finalist. He is also an associate editor for the journals Operations Research and Queueing Systems, a member of the INFORMS Applied Probability Society Council, and a Georgia Tech Class of 1969 Teaching fellow. More information about David and his research can be found on his website at http://www2.isye.gatech.edu/~dgoldberg9/