Canonical dual approach to solving the maximum cut problem

Zhenbo Wang (), Shu-Cherng Fang (), David Gao () and Wenxun Xing ()

Journal of Global Optimization, 2012, vol. 54, issue 2, 351 pages

Abstract: This paper presents a canonical dual approach for finding either an optimal or approximate solution to the maximum cut problem (MAX CUT). We show that, by introducing a linear perturbation term to the objective function, the maximum cut problem is perturbed to have a dual problem which is a concave maximization problem over a convex feasible domain under certain conditions. Consequently, some global optimality conditions are derived for finding an optimal or approximate solution. A gradient decent algorithm is proposed for this purpose and computational examples are provided to illustrate the proposed approach. Copyright Springer Science+Business Media, LLC. 2012

Keywords: Global optimization; Maximum cut; Canonical duality; Perturbation method (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10898-012-9881-8

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