A memetic approach for the max-cut problem

Authors:
Qinghua Wu;Jin-Kao Hao
Affiliations:
LERIA, Université d'Angers, Angers Cedex 01, France;LERIA, Université d'Angers, Angers Cedex 01, France
Venue:
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Year:
2012

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Abstract

The max-cut problem is to partition the vertices of a weighted graph G=(V,E) into two subsets such that the weight sum of the edges crossing the two subsets is maximized. This paper presents a memetic max-cut algorithm (MACUT) that relies on a dedicated multi-parent crossover operator and a perturbation-based tabu search procedure. Experiments on 30 G-set benchmark instances show that MACUT competes favorably with 6 state-of-the-art max-cut algorithms, and for 10 instances improves on the best known results ever reported in the literature.