Professor of Engineering Systems, Engineering Systems Division
and the Department of Civil and Environmental Engineering
Massachusetts Institute of Technology
Title: Online Resource Allocation with Applications to Revenue Management
Online resource allocation is a fundamental problem in OR and CS with applications such as offering products to customers, distributing jobs to candidates, assigning advertisers to ad slots, and matching drivers to passengers. These problems can be abstracted as follows: there are fixed resources, each of which can be sold at multiple known prices. These resources must be allocated on-the-fly, without assuming anything about future demand. In this talk we cover the CS and OR literature on the problem and in particular focus on two techniques: exploration and exploitation methods, as well as competitive analysis.
In the latter case, we review new algorithms that achieve tight competitive ratios under the integral or asymptotic settings. Our algorithms are simple, intuitive and robust and our competitive ratios are provably optimal, for every possible set of prices.
In the former case, we discuss an efficient and effective dynamic pricing algorithm, which builds upon the Thompson sampling algorithm used for multi-armed bandit problems by incorporating inventory constraints into the pricing decisions. The algorithm proves to have both strong theoretical performance guarantees as well as promising numerical performance results when compared to other algorithms developed for the same setting.
Finally, we compare the performance of both techniques, exploration and exploitation methods and competitive analysis, with real-world and synthetic data from various retail applications.
Professor of Operations Management, Area Leader (Operations Management) and
Senior Advisor (Faculty & Research) to the Dean
Indian School of Business
Title: Operations Management research to determine Support Prices in Agriculture
In this talk I shall describe an application of Operations Management models in agriculture.
The application deals with the problem of setting the minimum support price for staple crops in India. First, I shall summarize a modeling framework that can be used to determine how minimum support price for staple crops affects the decisions of farmers and consumers.
Next, how the optimal support price could be chosen using the framework? Then, I shall present calculations based on production data, storage and price information to determine the welfare-loss due to deviation from the optimal price. I shall also present extensions possible within the framework.