IIM PHD WORKSHOP by Professor Michael PINEDO and Ms. Yuqian XU
IIM PHD WORKSHOP
January 11, 2016 (Monday)
Part 1: 2:00p.m. – 4:00p.m.
Speaker: Professor Michael PINEDO (Julius Schlesinger Professor of Operations Management, Leonard N. Stern School of Business, New York University)
Title: Planning and Scheduling in the Service Industries
Abstract: This workshop focuses on some recent advances in planning and scheduling in the service industries. The planning and scheduling models in service environments as well as the solution methodologies tend to be different from those used in manufacturing environments. We describe five classes of models, the current status quo, and potential research directions. The first class considered includes interval scheduling models and reservation systems. The second class involves timetabling and tournament scheduling. The third class consists of transportation models (including aircraft routing and scheduling and train timetabling). The fourth class of models concern scheduling in health care, in particular appointment scheduling. The fifth and last class are the workforce scheduling models, shift scheduling as well as crew scheduling models. We conclude with a summary of the similarities and the differences between the model formulations and the solution techniques that are used in these various different areas.
January 11, 2016 (Monday)
Part 2: 4:00p.m. – 5:00p.m.
Speaker: Ms. Yuqian XU (Department of Information, Operations & Management Sciences, Leonard N. Stern School of Business, New York University)
Title: On the Modeling of Operational Risk in Finance
Abstract: In this talk, we first introduce a general framework that describes and analyzes operational risk models from an Operations Management perspective. Then we focus on two particular topics within this framework that deal with static and dynamic stochastic resource allocation models. Both models consider how to make optimal investments in different stochastic settings. In the static model, we mainly discuss the asymptotic behavior of investments. We quantify the optimal investments in both heavy trading regime and light trading regime, and provide managerial insights. In the dynamic model, we characterize a finite horizon, continuous trading setting with operational risk events arrive as a compound Poisson process. We study the dynamic budget allocation problem in this setting to mitigate the operational risk losses and to maximize the firm value as well as minimize the bankruptcy probability.