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

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    Type
    Article
    Authors
    Lima, Ricardo cc
    Grossmann, Ignacio E.
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2016-06-16
    Online Publication Date
    2016-06-16
    Print Publication Date
    2017-01
    Permanent link to this record
    http://hdl.handle.net/10754/621502
    
    Metadata
    Show full item record
    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
    Citation
    Lima RM, Grossmann IE (2016) On the solution of nonconvex cardinality Boolean quadratic programming problems: a computational study. Comput Optim Appl. Available: http://dx.doi.org/10.1007/s10589-016-9856-7.
    Sponsors
    Fundação para a Ciência e a Tecnologia[DFRH/WIIA/67/2011]
    European Union Seventh Framework Programme[PCOFUND-GA-2009-246542]
    Publisher
    Springer Nature
    Journal
    Computational Optimization and Applications
    DOI
    10.1007/s10589-016-9856-7
    ae974a485f413a2113503eed53cd6c53
    10.1007/s10589-016-9856-7
    Scopus Count
    Collections
    Articles; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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