A discrete filled function algorithm embedded with continuous approximation for solving max-cut problems

Ai-Fan Ling, Cheng-Xian Xu and Feng-Min Xu

European Journal of Operational Research, 2009, vol. 197, issue 2, 519-531

Abstract: In this paper, a discrete filled function algorithm embedded with continuous approximation is proposed to solve max-cut problems. A new discrete filled function is defined for max-cut problems, and properties of the function are studied. In the process of finding an approximation to the global solution of a max-cut problem, a continuation optimization algorithm is employed to find local solutions of a continuous relaxation of the max-cut problem, and then global searches are performed by minimizing the proposed filled function. Unlike general filled function methods, characteristics of max-cut problems are used. The parameters in the proposed filled function need not to be adjusted and are exactly the same for all max-cut problems that greatly increases the efficiency of the filled function method. Numerical results and comparisons on some well known max-cut test problems show that the proposed algorithm is efficient to get approximate global solutions of max-cut problems.

Keywords: Combinatorial; optimization; Global; optimization; Filled; function; Max-cut; Continuation; method; Local; search (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:197:y:2009:i:2:p:519-531

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