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Learning, Conjoint Analysis, and Binary Quadratic Optimization

Joe Naoum-Sawaya
Data dell'evento: 
Martedì, 11 June, 2019 - 12:00
Aula A4 - DIAG

In this talk, we present a learning approach to find good solutions for Binary Quadratic Programming. The proposed approach is based on learning a linear objective function which can then be used to optimize a linear binary program that provides a good feasible solution for the binary quadratic program and is computationally cheaper. The learning approach is inspired from conjoint analysis which can be formulated as a convex quadratic program. Computational results comparing the proposed approach to solving binary quadratic programs using CPLEX are presented.

gruppo di ricerca: 
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