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    • Revista IJIMAI
    • 2016
    • vol. 4, nº 2, december 2016
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    • Revista IJIMAI
    • 2016
    • vol. 4, nº 2, december 2016
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    Genetic Algorithm for Restricted Maximum k-Satisfiability in the Hopfield Network

    Autor: 
    Kasihmuddin, Mohd Shareduwan Bin Mohd
    ;
    Mansor, Mohd Asyraf Bin
    ;
    Sathasivam, Saratha
    Fecha: 
    12/2016
    Palabra clave: 
    genetic algorithms; neural network; hopfield; K-satisfiability; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/11702
    DOI: 
    http://doi.org/10.9781/ijimai.2016.429
    Dirección web: 
    https://ijimai.org/journal/bibcite/reference/2581
    Open Access
    Resumen:
    The restricted Maximum k-Satisfiability MAX- kSAT is an enhanced Boolean satisfiability counterpart that has attracted numerous amount of research. Genetic algorithm has been the prominent optimization heuristic algorithm to solve constraint optimization problem. The core motivation of this paper is to introduce Hopfield network incorporated with genetic algorithm in solving MAX-kSAT problem. Genetic algorithm will be integrated with Hopfield network as a single network. The proposed method will be compared with the conventional Hopfield network. The results demonstrate that Hopfield network with genetic algorithm outperforms conventional Hopfield networks. Furthermore, the outcome had provided a solid evidence of the robustness of our proposed algorithms to be used in other satisfiability problem.
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