Mohd Shareduwan Mohd Kasihmuddin, Mohd Asyraf Mansor and Saratha Sathasivam
Pertanika Journal of Science & Technology, Volume 25, Issue 1, January 2017
Keywords: Genetic Algorithm, Exhaustive Search, Hopfield network, Satisfiability, Logic Programming, HORN-SAT, 3-SAT, 2-SAT
Published on: 31 JANUARY 2017
In this study, a hybrid approach that employs Hopfield neural network and a genetic algorithm in doing k-SAT problems was proposed. The Hopfield neural network was used to minimise logical inconsistency in interpreting logic clauses or programme. Hybrid optimisation made use of the global convergence advantage of the genetic algorithm to deal with learning complexity in the Hopfield network. The simulation incorporated with genetic algorithm and exhaustive search method with different k-Satisfiability (k-SAT) problems, namely, the Horn-Satisfiability (HORN-SAT), 2-Satisfiability (2-SAT) and 3-Satisfiability (3-SAT) will be developed by using Microsoft Visual C++ 2010 Express Software. The performance of both searching techniques was evaluated based on global minima ratio, hamming distance and computation time. Simulated results suggested that the genetic algorithm outperformed exhaustive search in doing k-SAT logic programming in the Hopfield network.
ISSN 0128-7680
e-ISSN 2231-8526