Canonical dual approach to solving 0-1 quadratic programming problems

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Date

2008-02

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Volume Title

Publisher

American Institute of Mathematical Sciences

Abstract

This paper presents a canonical duality theory for solving nonconvex polynomial programming problems subjected to box constraints. It is proved that under certain conditions, the constrained nonconvex problems can be converted to the so-called canonical (perfect) dual problems, which can be solved by deterministic methods. Both global and local extrema of the primal problems can be identified by a triality theory proposed by the author. Applications to nonconvex integer programming and Boolean least squares problems are discussed. Examples are illustrated. A conjecture on NP-hard problems is proposed.

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Keywords

global optimization, duality, nonconvex minimization, box constraints, integer programming, boolean least squares problem, np-hard problems, global optimization, convex underestimators, triality theory, duality-theory, engineering, multidisciplinary, operations research & management, science, mathematics, interdisciplinary applications

Citation

Fang, S. C.; Gao, D. Y.; Sheu, R. L.; Wu, S. Y., "Canonical dual approach to solving 0-1 quadratic programming problems," J. Industrial and Management Optimization 4(1), 125-142, (2008); DOI: 10.3934/jimo.2008.4.125