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Non-convex mixed-integer nonlinear programming: a survey

Burer, S and Letchford, Adam (2012) Non-convex mixed-integer nonlinear programming: a survey. Surveys in Operations Research and Management Science, 17 (2). pp. 97-106. ISSN 1876-7354

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    Abstract

    A wide range of problems arising in practical applications can be formulated as Mixed-Integer Nonlinear Programs (MINLPs). For the case in which the objective and constraint functions are convex, some quite effective exact and heuristic algorithms are available. When nonconvexities are present, however, things become much more difficult, since then even the continuous relaxation is a global optimisation problem. We survey the literature on non-convex MINLP, discussing applications, algorithms and software. Special attention is paid to the case in which the objective and constraint functions are quadratic.

    Item Type: Article
    Journal or Publication Title: Surveys in Operations Research and Management Science
    Uncontrolled Keywords: mixed-integer nonlinear programming ; global optimisation
    Subjects: H Social Sciences > HB Economic Theory
    Departments: Lancaster University Management School > Management Science
    ID Code: 56113
    Deposited By: ep_importer_pure
    Deposited On: 13 Jul 2012 13:27
    Refereed?: Yes
    Published?: Published
    Last Modified: 06 Feb 2013 17:25
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/56113

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