Prof. Nilay Noyan: Two-stage Stochastic Programming under Multivariate Risk Constraints – In this study, we consider two classes of multicriteria two-stage stochastic programs in finite probability spaces with multivariate risk constraints. The first-stage problem features a multivariate stochastic benchmarking constraint based on a vector-valued random variable representing multiple and possibly conflicting stochastic performance measures associated with… [read more]

On Tuesday, June 29, 2021, Alexandre Forel successfully defended his PhD thesis entitled "Rolling-horizon production planning for seasonal and uncertain demand". It was the fourth defense at AdONE. Congratulations, Alexandre! [read more]

Prof. Itai Ashlagi (Stanford University): Stochastic Price Adaptation, Waiting Lists, and Stochastic Gradient Descent – Waiting lists allocate items by offering agents a choice among items with associated waiting times. These waiting times serve as prices that are determined endogenously and adjust according to the stochastic arrivals and departures of agents. We study the allocative efficiency under such dynamically adjusting prices by drawing a… [read more]

On Thursday, June 24, 2021, Marilena Leichter successfully defended her PhD thesis, which is entitled "Combinatorial Algorithms for Covering and Scheduling Problems". It was the third defense at AdONE. Congratulations, Marilena! [read more]

Prof. Tugce Martagan (School of Industrial Engineering, Eindhoven University of Technology): Improving Access to New Biopharmaceuticals: Operational and Strategic Insights – More than 8,000 therapeutics are in the global biopharmaceutical research and development pipeline to treat cancer, diabetes, and many other diseases. These therapeutics are the “next-generation" drugs produced by biomanufacturing technologies. Unlike traditional pharmaceuticals that… [read more]

Prof. Prof. Serpil Sayın (Koç University): Representations of the Nondominated Set in Multiobjective Optimization – The solution to a multiobjective optimization problem consists of the nondominated set that portrays all relevant trade-off information. This set is often difficult to obtain and present to a Decision Maker. Therefore it makes sense to try to identify a Decision Maker’s most preferred solution without generating the entire nondominated set;… [read more]

On Wednesday, March 24th, Richard Littmann, the second PhD student from AdONE to do so, successfully defended his PhD thesis. Congratulations! His thesis is titled "Pricing in Non-Convex Markets". We wish you all the best for your future, Richard! [read more]

Prof. Simge Küçükyavuz (Northwestern University): Mixed-Integer Convex Programming for Statistical Learning – In the first part of this talk, we consider the problem of learning an optimal directed acyclic graph (DAG) from continuous observational data. We cast this problem in the form of a mathematical programming model which can naturally incorporate a super-structure to reduce the set of candidate DAGs. We use the penalized negative log-likelihood score… [read more]

Prof. Ho-Yin Mak (University of Oxford): Dimensionality Reduction for Stochastic Optimization – Modern data science applications often involve high-dimensional data. A common approach involves first performing dimensionality reduction on the data, and then subsequently solving the optimization problem with the low-dimensional representation. However, standard dimensionality reduction methods are designed to maximize the amount of information retained in… [read more]

Prof. Reha Uzsoy (North Carolina State University): Fast Approximate Solutions for Capacitated Production Planning Under Uncertain Demand – The effective management of supply chains producing physical goods requires coordination of the production systems manufacturing the goods, the inventories held for different reasons throughout the supply chain and the logistics systems that move the goods from origin to destination. Despite the evident… [read more]