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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: 12 Dec 2017 04:39
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/56113

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