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Evolutionary algorithms for the satisfiability problem.

Jens Gottlieb1, Elena Marchiori, Claudio Rossi

  • 1SAP AG, Neurottstrasse 16, 69190 Walldorf, Germany. jens.gottlieb@sap.com

Evolutionary Computation
|March 26, 2002
PubMed
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Evolutionary algorithms using bit string representations show competitive performance against WSAT for solving the Boolean satisfiability problem. This study offers guidelines for developing effective evolutionary heuristics.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Computational Complexity

Background:

  • The Boolean satisfiability problem (SAT) is a fundamental challenge in computer science.
  • Various evolutionary algorithms (EAs) have been explored for SAT.
  • Solution representation is crucial for EA performance.

Purpose of the Study:

  • To review and evaluate solution representations for EAs applied to SAT.
  • To empirically compare prominent EAs with the local search algorithm WSAT.
  • To identify key features of successful EAs for SAT.

Main Methods:

  • Literature review of solution representations for EAs in SAT.
  • Selection of the bit string representation for empirical evaluation.
  • Comparative analysis of top-performing EAs against WSAT on standard benchmarks.

Related Experiment Videos

Main Results:

  • The bit string representation is identified as a promising approach for EAs in SAT.
  • Evolutionary algorithms demonstrate competitive performance compared to WSAT.
  • Key characteristics of effective EAs for SAT are elucidated.

Conclusions:

  • Evolutionary algorithms, particularly with bit string representations, are viable and competitive for solving SAT.
  • The findings provide methodological guidelines for designing novel SAT heuristics.
  • This research contributes to the understanding of EAs in the context of constraint satisfaction problems.