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“Meet a GERAD researcher!” seminar

Learning a classification of mixed-integer quadratic programming problems


Nov 14, 2017   03:45 PM — 05:00 PM

Giulia Zarpellon Polytechnique Montréal, Canada

Within state-of-the-art optimization solvers such as IBM-CPLEX the ability to solve both convex and nonconvex Mixed-Integer Quadratic Programming (MIQP) problems to proven optimality goes back few years, but still presents unclear aspects. We are interested in understanding whether for solving an MIQP problem it is favorable to linearize its quadratic part or not. Our approach employs Machine Learning techniques to learn a classifier that predicts, for a given MIQP instance, the most suitable resolution method within IBM-CPLEX's algorithmic framework. We aim as well at gaining methodological insights about the instances' features leading this discrimination. Together with a new generated dataset, we examine part of CPLEX internal testbed and discuss different learning scenarios to integrate learning and optimization processes. By defining novel measures, we interpret learning results and evaluate the quality of the tested classifiers from the optimization point of view.

(Joint work with Pierre Bonami and Andrea Lodi)

Coffee and biscuits will be offered at the beginning of the seminar.
Welcome to everyone!

Georges Zaccour organizer


Room 4488
André-Aisenstadt Building
Université de Montréal Campus
2920, chemin de la Tour Montréal QC H3T 1J4 Canada