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Improving configuration checking for satisfiable random k-SAT instances

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Abstract

Local search algorithms based on the Configuration Checking (CC) strategy have been shown to be efficient in solving satisfiable random k-SAT instances. The purpose of the CC strategy is to avoid the cycling problem, which corresponds to revisiting already flipped variables too soon. It is done by considering the neighborhood of the formula variables. In this paper, we propose to improve the CC strategy on the basis of an empirical study of a powerful algorithm using this strategy. The first improvement introduces a new and simple criterion, which refines the selection of the variables to flip for the 3-SAT instances. The second improvement is achieved by using the powerful local search algorithm Novelty with the adaptive noise setting. This algorithm enhances the efficiency of the intensification and diversification phases when solving k-SAT instances with k ≥ 4. We name the resulting local search algorithm Ncca+ and show its effectiveness when treating satisfiable random k-SAT instances issued from the SAT Challenge 2012. Ncca+ won the bronze medal of the random SAT track of the SAT Competition 2013.

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Authors and Affiliations

  1. Aix Marseille Université, CNRS, ENSAM, Université de Toulon, LSIS UMR 7296, 13397, Marseille, France

    André Abramé, Djamal Habet & Donia Toumi

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  1. André Abramé
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  2. Djamal Habet
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  3. Donia Toumi
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Correspondence to Djamal Habet.

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Abramé, A., Habet, D. & Toumi, D. Improving configuration checking for satisfiable random k-SAT instances. Ann Math Artif Intell 79, 5–24 (2017). https://doi.org/10.1007/s10472-016-9515-9

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