Abstract
It has been shown that simple evolutionary algorithms are able to solve the minimum cut problem in expected polynomial time when using a multi-objective model of the problem. In this paper, we generalize these ideas to the NP-hard minimum multicut problem. Given a set of k terminal pairs, we prove that evolutionary algorithms in combination with a multi-objective model of the problem are able to obtain a k-approximation for this problem in expected polynomial time.
This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center “Computational Intelligence” (SFB 531).
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Neumann, F., Reichel, J. (2008). Approximating Minimum Multicuts by Evolutionary Multi-objective Algorithms. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_8
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DOI: https://doi.org/10.1007/978-3-540-87700-4_8
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