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Combining cellular genetic algorithms and local search for solving satisfiability problems

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3 Author(s)
Folino, G. ; ISI, Calabria Univ., Italy ; Pizzuti, C. ; Spezzano, G.

A new parallel hybrid method for solving the satisfiability problem that combines cellular genetic algorithms and the random walk (WSAT) strategy of GSAT is presented. The method, called CGWSAT, uses a cellular genetic algorithm to perform a global search on a random initial population of candidate solutions and a local selective generation of new strings. Global search is specialized in local search by adopting the WSAT strategy. CGWSAT has been implemented on a Meiko CS-2 parallel machine using a two-dimensional cellular automaton as a parallel computation model. The algorithm has been tested on randomly generated problems and some classes of problems from the DIMACS test set

Published in:

Tools with Artificial Intelligence, 1998. Proceedings. Tenth IEEE International Conference on

Date of Conference:

10-12 Nov 1998

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