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The '''Karloff–Zwick algorithm''', in [[computational complexity theory]], is a [[randomized algorithm|randomised]] [[approximation algorithm]] taking an instance of [[MAX-3SAT]] [[Boolean satisfiability problem]] as input. If the instance is satisfiable, then the expected weight of the assignment found is at least 7/8 of optimal. There is strong evidence (but not a [[mathematical proof]]) that the algorithm
The algorithm is based on [[semidefinite programming]]. It can be derandomized using, e.g., the techniques from <ref>{{citation|last1=Sivakumar |first1=D. |title=Proceedings of the thiry-fourth annual ACM symposium on Theory of computing |chapter=Algorithmic derandomization via complexity theory |date=19 May 2002 |pages=619–626 |doi=10.1145/509907.509996|isbn=1581134959 |s2cid=94045 }}</ref> to yield a deterministic [[polynomial-time]] algorithm with the same approximation guarantees.
==Comparison to random assignment==
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==Optimality==
Building upon previous work on the [[PCP theorem]], [[Johan Håstad]] showed that, assuming P ≠ NP, no polynomial-time algorithm for MAX 3SAT can achieve a performance ratio exceeding 7/8, even when restricted to satisfiable instances of the problem in which each clause contains exactly three literals. Both the Karloff–Zwick algorithm and the above simple algorithm are therefore optimal in this sense.<ref>{{citation|first=J.|last=Hastad|title=Some optimal inapproximability results|journal=[[Journal of the ACM]]|volume=48|issue=4|year=2001|doi=10.1145/502090.502098|pages=798–859|citeseerx=10.1.1.638.2808|s2cid=5120748 }}.</ref>
== References ==
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