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Approximating Max kCSP – Outperforming a Random Assignment with Almost a Linear Factor

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3580))

Abstract

An instance of Max kCSP consists of weighted k-ary constraints acting over a set of Boolean variables. The objective is to find an assignment to the Boolean variables such that the total weight of satisfied constraints is maximized. In this paper we provide a probabilistical polynomial time approximation algorithm that c 0 k(log k)− 1 2\(^{\rm -{\it k}}\)-approximates Max kCSP, for a constant c 0>0.

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© 2005 Springer-Verlag Berlin Heidelberg

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Hast, G. (2005). Approximating Max kCSP – Outperforming a Random Assignment with Almost a Linear Factor. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds) Automata, Languages and Programming. ICALP 2005. Lecture Notes in Computer Science, vol 3580. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11523468_77

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  • DOI: https://doi.org/10.1007/11523468_77

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27580-0

  • Online ISBN: 978-3-540-31691-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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