SMMH - A parallel Heuristic for combinatorial optimization problems

Guilherme Domingues, Yoshiyuki Morie, Feng Long Gu, Takeshi Nanri, Kazuaki Murakami

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The process of finding one or more optimal solutions for answering combinatorial optimization problems bases itself on the use of algorithms instances. Those instances usually have to explore a very large search spaces. Heuristics search focusing on the use of High-Order Hopfield neural networks is a largely deployed technique for very large search space. It can be established a very powerful analogy towards the dynamics evolution of a physics spin-glass system while minimizing its own energy and the energy function of the network. This paper presents a new approach for solving combinatorial optimization problems through parallel simulations, based on a High-Order Hopfield neural network using MPI specification.

    Original languageEnglish
    Title of host publicationComputation in Modern Science and Engineering - Proceedings of the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007)
    Pages40-43
    Number of pages4
    Edition2
    DOIs
    Publication statusPublished - Dec 1 2007
    EventInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007 - Corfu, Greece
    Duration: Sep 25 2007Sep 30 2007

    Publication series

    NameAIP Conference Proceedings
    Number2
    Volume963
    ISSN (Print)0094-243X
    ISSN (Electronic)1551-7616

    Other

    OtherInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007
    CountryGreece
    CityCorfu
    Period9/25/079/30/07

    All Science Journal Classification (ASJC) codes

    • Ecology, Evolution, Behavior and Systematics
    • Ecology
    • Plant Science
    • Physics and Astronomy(all)
    • Nature and Landscape Conservation

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