Discrete Optimization Talks (DOTs)
DOTs are virtual discrete optimization talks, organized by Aleksandr M. Kazachkov and Elias B. Khalil. To receive updates (and the Zoom link) for upcoming DOTs, please join our mailing list. If you would like to give a DOT, please fill out this form or email us.
Topics of interest include theoretical, computational, and applied aspects of integer and combinatorial optimization.
The format is two 30-minute talks each session. From February to April 2023, the seminars are scheduled the last Friday of every month at 12:00 p.m. ET.
A special feature of DOTs is a social component. After a usual talk, you might grab a tea/coffee and chat with other attendees. Why not here too? Join us for some informal discussion after each DOT, as well as throughout the week on our Discord channel.
Videos of past DOTs are posted under Past Talks and can also be found on our YouTube Channel.
Join the mailing list to receive information about our upcoming seminars and how to virtually participate. Joining this list is necessary to receive the password for each DOT (usually sent on the Monday of the week in which there are DOTs). You may also wish to subscribe to our Google calendar (also available in ics format).
Upcoming Talks
Convex integer nonlinear programming for maximum-entropy sampling
Abstract: The maximum-entropy sampling problem (MESP) aims to find a subset of given size s, from a set of correlated Gaussian random variables, with maximum differential entropy. Given the covariance matrix for the multivariate Gaussian vector, MESP is equivalent to maximizing the determinant of an order-s principal submatrix. MESP has application to the problem of designing environmental-monitoring networks. The problem is NP-hard and challenging from the perspective of integer nonlinear optimization. I will give an overview of the development of convex integer nonlinear programming formulations of the problem to be used in exact algorithmic approaches.
Mitigating New Threats to the Global Drug Supply: Supply Chain Design under Geopolitical Strain
Abstract: Pharmaceutical supply chains have experienced on-going struggles to meet the domestic and global demand for drugs for decades. Shortages are caused by supply-demand mismatches and supply strain, including disruptions due to quality and natural disasters. A recent strain – export bans – has emerged as a result of recent geopolitical instability and persistent shortages. These may be mitigated by strategic alliances, but effects on design decisions are unknown. In this work, we present one of the first global supply chain design models for the pharmaceutical industry. It uses a stochastic integer programming approach to optimize a company’s supply chain under geopolitical strain, endogenous pricing, strategic alliances, and global demand. We evaluate effects on countries by income level and analyze policies to improve global access.
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For questions or suggestions, please contact Aleksandr M. Kazachkov or Elias B. Khalil.
DOTs are supported by the Canada Excellence Research Chair in Data Science for Real-Time Decision-Making and the University of Florida Department of Industrial and Systems Engineering.
