The study of scheduling problems has a long history in the academic literature.  However, many classic models used to study scheduling problems do not incorporate customer impatience.  Furthermore, many of the ones that do assume the time a customer is willing to wait for service is exponentially distributed.  The issue is that that assumption can…

Retailers typically use assortment planning to maximize store profits given product characteristics. We study the manufacturers' price-setting interactions and how these can be manipulated by the retailer's assortment strategy. We show that constraining the breadth of the assortment has two main effects on retailer profits: first, a larger assortment may intensify competitive pressure and decrease…

We develop a novel, data-driven approach to deal with appointment sequencing and scheduling in a multi-server system, where both customer punctuality and service times are stochastic. Our model is calibrated using a data set of unprecedented resolution, gathered at a large-scale outpatient oncology practice. This data set combines real-time locations, electronic health records and appointments…

During this talk I will present a queuing model for database locking systems, where jobs represent user requests for simultaneous access to a set of files in a large database. While files are in use, their content can change, so to preserve consistency throughout the database files currently in use are locked, creating blocking and…

This paper studies the valuation of American options for a general one-factor stochastic volatility model.  Using the local time-space calculus on surfaces we derive an early exercise premium representation for the option price, parametrized by the optimal exercise surface. The exercise surface is the unique solution to an integral equation of Volterra type. The paper…

Kornelia Bastin, OR PhD Student People are faced with an overwhelming amount of news, only some of which comes from credible sources and is fact verified. The main idea behind this project is to address such issues. The scope of work includes creating an accessible and efficient method for members of the public to get…

Matrix computations are ubiquitous in scientific computing and data science. However, many existing methods consume enormous computational resources for solving increasingly large and complex problems. In this talk, I will describe my work on exploiting mathematical structures and hardware capabilities to accelerate matrix computations. I will focus on a randomized algorithm, namely RChol, for computing…