Cooperative bees swarm for solving the maximum weighted satisfiability problem

  • Authors:

  • Habiba Drias;Souhila Sadeg;Safa Yahi

  • Affiliations:

  • INI, National Institute of Informatics;Computer Science department, Laboratory of research in Artificial Intelligence, USTHB, Algiers, Algeria;Computer Science department, Laboratory of research in Artificial Intelligence, USTHB, Algiers, Algeria

  • Venue:
  • IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

Solving a NP-Complete problem precisely is spiny: the combinative explosion is the ransom of this accurateness. It is the reason for which we have often resort to approached methods assuring the obtaining of a good solution in a reasonable time. In this paper we aim to introduce a new intelligent approach or meta-heuristic named “Bees Swarm Optimization”, BSO for short, which is inspired from the behaviour of real bees. An adaptation to the features of the MAX-W-SAT problem is done to contribute to its resolution. We provide an overview of the results of empirical tests performed on the hard Johnson benchmark. A comparative study with well known procedures for MAX-W-SAT is done and shows that BSO outperforms the other evolutionary algorithms especially AC-SAT, an ant colony algorithm for SAT.