On the solution of nonconvex cardinality Boolean quadratic programming problems: a computational study

Ricardo Lima, Ignacio E. Grossmann

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Original languageEnglish (US)
Pages (from-to)1-37
Number of pages37
JournalComputational Optimization and Applications
Volume66
Issue number1
DOIs
StatePublished - Jun 16 2016

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