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Solving sparse instances of Max SAT via width reduction and greedy restriction. (English) Zbl 1347.68312
Summary: We present a moderately exponential time and polynomial space algorithm for sparse instances of Max SAT. Our algorithms run in time of the form \(O\left (2^{(1-\mu (c))n}\right )\) for instances with \(n\) variables and cn clauses. Our deterministic and randomized algorithm achieve \(\mu (c) = {\varOmega }\left (\frac {1}{c^{2}\log ^{2} c}\right )\) and \(\mu (c) = {\varOmega }\left (\frac {1}{c \log ^{3} c}\right )\) respectively. Previously, an exponential space deterministic algorithm with \(\mu (c) = {\varOmega }\left (\frac {1}{c\log c}\right )\) was shown by E. Dantsin and A. Wolpert [Lect. Notes Comput. Sci. 4121, 266–276 (2006; Zbl 1187.68258)] and a polynomial space deterministic algorithm with \(\mu (c) = {\varOmega }\left (\frac {1}{2^{O(c)}}\right )\) was shown by A. S. Kulikov and K. Kutzkov [Lect. Notes Comput. Sci. 4649, 194–204 (2007; Zbl 1188.68272)]. Our algorithms have three new features. They can handle instances with (1) weights and (2) hard constraints, and also (3) they can solve counting versions of Max SAT. Our deterministic algorithm is based on the combination of two techniques, width reduction of Schuler and greedy restriction of Santhanam. Our randomized algorithm uses random restriction instead of greedy restriction.

MSC:
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68Q25 Analysis of algorithms and problem complexity
Software:
MAX-2-SAT
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