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A variable neighborhood Walksat-based algorithm for MAX-SAT problems.

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This study introduces a novel variable neighborhood Walksat algorithm for the maximum satisfiability (MAX-SAT) problem. The new approach enhances clause satisfaction compared to traditional 1-flip methods.

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Area of Science:

  • Artificial Intelligence
  • Computer Science
  • Optimization

Background:

  • The Maximum Satisfiability (MAX-SAT) problem is a fundamental NP-complete optimization problem with broad applications in AI and computing.
  • Local search algorithms, particularly Walksat, are widely used for MAX-SAT, typically employing a 1-flip neighborhood structure.

Purpose of the Study:

  • To introduce a novel Walksat-based algorithm utilizing a variable neighborhood structure for MAX-SAT.
  • To evaluate the effectiveness of this new algorithm against existing 1-flip neighborhood methods.

Main Methods:

  • Development of a Walksat algorithm incorporating a variable neighborhood structure.
  • Comparative analysis against established algorithms like CCLS and Optimax using the 1-flip neighborhood.

Main Results:

  • The variable neighborhood approach demonstrated improved performance in MAX-SAT evaluations.
  • The algorithm's effectiveness was validated against leading solvers in the field.

Conclusions:

  • Variable neighborhood structures offer a promising enhancement for Walksat-based MAX-SAT solvers.
  • The proposed algorithm presents a competitive alternative to existing methods for solving MAX-SAT instances.