Events Calendar

Epstein ISE Department Seminar

Speaker: Phebe Vayanos, Lecturer and Postdoctoral Associate, MIT Operations Research Center

Talk Title: Data-Driven Learning Under Uncertainty: An Adaptive Optimization Perspective

Abstract: Motivated by the recent explosion of data availability and the plethora of decision problems affected by uncertainty, we propose a data-driven paradigm for dynamic learning that unifies optimization and estimation. Our framework naturally captures the critical exploration-exploitation trade-off of the decision-maker, and we develop a tractable solution scheme to compute near-optimal policies. We showcase the versatility of our method by applying it to two very diverse areas: we focus on a pricing problem arising in revenue management and then discuss an application in energy.

In the area of revenue management, we discuss the pricing problem faced by a retailer who has a finite inventory of a product available for sale. We assume that the product demand curve is unknown to the retailer who has at his disposal a history of sales data. We present computational results that show that our proposed policies: (a) yield higher profits compared to commonly used policies, (b) nearly match results obtained with perfect information under downside measures such as Conditional Value-at-Risk, and (c) can be obtained in modest computational time for large-scale problems.

In the area of energy, we discuss an industrial application of our research in collaboration with BP, one of the world’s major oil and gas companies. Using actual data from a BP oilfield, we create a simple and powerful model for predicting oil production that circumvents the need for complex reservoir modeling. We leverage this model and the framework described above to devise a methodology that enables oil companies to maximize the quantities of oil extracted from each reservoir, and therefore decrease the natural resources (and energy supplies) that are left untapped.

This is joint work with Dimitris Bertsimas, MIT.


Biography: Phebe Vayanos is a lecturer in the Operations Research and Statistics Group at MIT Sloan School of Management, and a postdoctoral research associate in the Operations Research Center at MIT. Her current research is focused on developing data-driven models and scalable solution approaches for real-world decision problems affected by uncertainty and ambiguity. In particular, she is motivated by applications in revenue management, energy, finance, education, and healthcare. She holds a PhD degree in Operations Research and an MEng degree in Electrical & Electronic Engineering, both from Imperial College London. She has extensive experience with the energy and investment banking industries, having worked at JPMorgan and BNP Paribas and having consulted for BP.

More Information: SEMINAR-Vayanos.doc

Location: Ethel Percy Andrus Gerontology Center (GER) - 206

Audiences: Everyone Is Invited

Contact: Georgia Lum