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    Wyświetlanie 1-4 z 4
    Tytuł:
    Comparative Study of Particle Swarm Optimization and Genetic Algorithms for Complex Mathematical Functions
    Autorzy:
    Valdez, F.
    Melin, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/384575.pdf
    Data publikacji:
    2008
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    genetic algorithms
    particle swarm optimization (PSO)
    hybrid systems
    optimization
    Opis:
    The Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA) have been used successfully in solving problems of optimization with continuous and combinatorial search spaces. In this paper the results of the application of PSO and GAs for the optimization of mathematical functions are presented. These two methodologies have been implemented with the goal of making a comparison of their performance in solving complex optimization problems. This paper describes a comparison between a GA and PSO for the optimization of complex mathematical functions.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 1; 43-51
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the hybridization of the artificial Bee Colony and Particle Swarm Optimization Algorithms
    Autorzy:
    El-Abd, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/91658.pdf
    Data publikacji:
    2012
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    Artificial Bee Colony Algorithm
    ABC
    particle swarm optimization (PSO)
    PSO
    hybridization
    hybrid algorithm
    CEC05
    Opis:
    In this paper we investigate the hybridization of two swarm intelligence algorithms; namely, the Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO). The hybridization technique is a component-based one, where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. Three different versions of the hybrid algorithm are tested in this work by experimenting with different selection mechanisms for the ABC component. All the algorithms are applied to the well-known CEC05 benchmark functions and compared based on three different metrics, namely, the solution reached, the success rate, and the performance rate.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 2; 147-155
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cellular particle swarm optimization with a simple adaptive local search strategy for the permutation flow shop scheduling problem
    Autorzy:
    Seck-Tuoh-Mora, Juan C.
    Medina-Marin, Joselito
    Martinez-Gomez, Erick S.
    Hernandez-Gress, Eva S.
    Hernandez-Romero, Norberto
    Volpi-Leon, Valeria
    Powiązania:
    https://bibliotekanauki.pl/articles/230060.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    flow shop
    particle swarm optimization (PSO)
    local search strategy
    hybrid search method
    cellular automata
    scheduling
    Opis:
    Permutation flow shop scheduling problem deals with the production planning of a number of jobs processed by a set of machines in the same order. Several metaheuristics have been proposed for minimizing the makespan of this problem. Taking as basis the previous Alternate Two-Phase PSO (ATPPSO) method and the neighborhood concepts of the Cellular PSO algorithm proposed for continuous problems, this paper proposes the improvement of ATPPSO with a simple adaptive local search strategy (called CAPSO-SALS) to enhance its performance. CAPSO-SALS keeps the simplicity of ATPPSO and boosts the local search based on a neighborhood for every solution. Neighbors are produced by interchanges or insertions of jobs which are selected by a linear roulette scheme depending of the makespan of the best personal positions. The performance of CAPSO-SALS is evaluated using the 12 different sets of Taillard’s benchmark problems and then is contrasted with the original and another previous enhancement of the ATPPSO algorithm. Finally, CAPSO-SALS is compared as well with other ten classic and state-of-art metaheuristics, obtaining satisfactory results.
    Źródło:
    Archives of Control Sciences; 2019, 29, 2; 205-226
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Hybrid MPPT algorithm for PV systems under partially shaded conditions using a stochastic evolutionary search and a deterministic hill climbing
    Autorzy:
    Basiński, K.
    Ufnalski, B.
    Grzesiak, L. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/1193446.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    maximum power point tracking
    photovoltaic system
    hybrid part-stochastic part-deterministic search rule
    particle swarm optimization (PSO)
    partial shading
    hill climbing
    Opis:
    A hybrid maximum power point tracking method has been proposed for the photovoltaic system using a stochastic evolutionary search and a deterministic hill climbing algorithm. The proposed approach employs the particle swarm optimizer (PSO) to solve a dynamic optimization problem related to the control task in a PV system. The position of the best particle is updated by the hill climbing algorithm, and the position of the rest of the particles by the classic PSO rule. The presented method uses the re-randomization mechanism, which places five consecutive particles randomly, but in specified intervals. This mechanism helps track the maximum power point under partially shaded conditions.
    Źródło:
    Power Electronics and Drives; 2017, 2, 37/2; 49-59
    2451-0262
    2543-4292
    Pojawia się w:
    Power Electronics and Drives
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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