Maximum stable set formulations and heuristics based on continuous optimization |
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Authors: | Samuel Burer Renato D.C. Monteiro Yin Zhang |
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Affiliation: | (1) Department of Management Sciences, University of Iowa, Iowa City, Iowa 52242, USA, e-mail: samuel-burer@uiowa.edu. This author was supported in part by NSF Grants CCR-9902010, CCR-0203426 and INT-9910084., US;(2) School of ISyE, Georgia Institute of Technology, Atlanta, Georgia 30332, USA, e-mail: monteiro@isye.gatech.edu. This author was supported in part by NSF Grants CCR-9902010, CCR-0203113 and INT-9910084., US;(3) Department of Computational and Applied Mathematics, Rice University, Houston, Texas 77005, USA, e-mail: zhang@caam.rice.edu. This author was supported in part by DOE Grant DE-FG03-97ER25331, DOE/LANL Contract 03891-99-23 and NSF Grant DMS-9973339., US |
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Abstract: | The stability number α(G) for a given graph G is the size of a maximum stable set in G. The Lovász theta number provides an upper bound on α(G) and can be computed in polynomial time as the optimal value of the Lovász semidefinite program. In this paper, we show that restricting the matrix variable in the Lovász semidefinite program to be rank-one and rank-two, respectively, yields a pair of continuous, nonlinear optimization problems each having the global optimal value α(G). We propose heuristics for obtaining large stable sets in G based on these new formulations and present computational results indicating the effectiveness of the heuristics. Received: December 13, 2000 / Accepted: September 3, 2002 Published online: December 19, 2002 RID="★" ID="★" Computational results reported in this paper were obtained on an SGI Origin2000 computer at Rice University acquired in part with support from NSF Grant DMS-9872009. Key Words. maximum stable set – maximum clique – minimum vertex cover – semidefinite program – semidefinite relaxation – continuous optimization heuristics – nonlinear programming Mathematics Subject Classification (2000): 90C06, 90C27, 90C30 |
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