Exponential lower bounds for DPLL algorithms on satisfiable random 3-CNF formulas

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Abstract

We consider the performance of a number of DPLL algorithms on random 3-CNF formulas with n variables and m = rn clauses. A long series of papers analyzing so-called "myopic" DPLL algorithms has provided a sequence of lower bounds for their satisfiability threshold. Indeed, for each myopic algorithm A it is known that there exists an algorithm-specific clause-density, r A, such that if r 2.78 and the same is true for generalized unit clause for all r > 3.1. Our results imply exponential lower bounds for many other myopic algorithms for densities similarly close to the corresponding rA. © 2012 Springer-Verlag.

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Achlioptas, D., & Menchaca-Mendez, R. (2012). Exponential lower bounds for DPLL algorithms on satisfiable random 3-CNF formulas. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7317 LNCS, pp. 327–340). https://doi.org/10.1007/978-3-642-31612-8_25

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