This research seminar on Machine Learning for Combinatorial Optimization was held on February 10, 2021 as part of the OPTIMAL (Optimization for and with Machine Learning) research project by Lara Scavuzzo (TU Delft). Ms Scavuzzo is PhD researcher within this project.
|Date||10 February 2021|
Within optimization solvers, such as Mixed Integer Programming (MIP) solvers, a large number of algorithmic choices have to be made. In many cases, there is little mathematical understanding on how to approach these decision-making problems efficiently. At the same time, these choices can have a critical impact on the speed of the solution process. For this reason, there is an interest in better decision strategies.
In this talk, we will discuss recent work in a growing line of research: incorporating Machine Learning (ML) tools into the solution process of optimization problems. The goal is to design optimization algorithms that exploit data to make better-informed decisions. We will start with a general overview of the progress in this field, to then focus on ML within MIP solvers.
The research project Optimization for and with Machine Learning (OPTIMAL) is an ENW-GROOT research project funded by NWO. It is a collaboration between researchers from Centrum Wiskunde & Informatica (CWI), Delft University of Technology (TU Delft) and the University of Amsterdam (UvA). It started in 2020 and will end in 2025. Research from this project will be shared in various events. For more information about this research project visit the project site OPTIMAL.uva.nl and the events calendar.