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Author: search.filters.author.Murillo-Suarez, AlfonsoSubject: search.filters.subject.Metaheuristics

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    Item type:Publication,
    MTGWA: A Multithreaded Gray Wolf Algorithm with Strategies Based on Simulated Annealing and Genetic Algorithms
    (2021)
    ;
    Murillo-Suarez, Alfonso
    ;
    García-Jacas, Cesar Raúl
    ;
    Guerrero-Valadez, Juan Manuel
    In this paper, we present an improvement of the Gray Wolf algorithm (GWO) based on a multi-threaded implementation of the original algorithm. The paper demonstrates how to combine the solutions obtained in each of the threads to achieve a final solution closer to the absolute minimum or even equal to it. To properly combine the solutions of each of the threads of execution, we use strategies based on simulated annealing and genetic algorithms. Also, we show the results obtained for twenty-nine functions: unimodal, multimodal, fixed dimension and composite functions. Experiments show that our proposed improves the results of the original algorithm. © Springer Nature
    Scopus© Citations 1  30  2
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    A new swarm algorithm for global optimization of multimodal functions over multi-threading architecture hybridized with simulating annealing
    (2018)
    ;
    Murillo-Suarez, Alfonso
    This paper presents a new algorithm, PCLPSO, based on particle swarm optimization, which uses comprehensive learning particle swarm optimizer. Our algorithm executes C parallel CLPSO algorithms. We adopted as a criterion of completion a maximum value of evaluations of the objective function. During the execution of the CLPSO algorithms, when a certain evaluation value of the functions is reached, the best k are selected, and different initialization criteria are applied to continue the execution of the CLPSO algorithms: restarting the worst ones for the best solution or restores the worst ones to a random solution. For this restart, we use the Boltzmann criterion in a similar way as Simulating Annealing (SA) does. In this work, the experimental results obtained for the search of the minimum of 16 multimodal test functions such as Rosenbrock, Griewank, Rastrigin, Brannin, Schwefel, and others. Our algorithm proved to be more efficient than the traditional CLPSO in its experimental results, and the nonparametric Wilcoxon test confirmed this.
    Scopus© Citations 7  18  1