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    Wyświetlanie 1-3 z 3
    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:
    An agent-oriented hierarchic strategy for solving inverse problems
    Autorzy:
    Smołka, M.
    Schaefer, R.
    Paszyński, M.
    Pardo, D.
    Álvarez-Aramberri, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/329764.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    inverse problem
    hybrid optimization method
    memetic algorithm
    multi-agent system
    magnetotelluric data inversion
    zadanie odwrotne
    optymalizacja hybrydowa
    algorytm memetyczny
    system wieloagentowy
    Opis:
    The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainly because the direct solver accuracy (performed by the hp-adaptive finite element method) is dynamically adjusted for each inverse search step. The computational cost is further decreased by the strategy employed for solution inter-processing and fitness deterioration. The HMS efficiency is compared with the results of a standard evolutionary technique, as well as with the multi-start strategy on benchmarks that exhibit typical inverse problems’ difficulties. Finally, an HMS application to a real-life engineering problem leading to the identification of oil deposits by inverting magnetotelluric measurements is presented. The HMS applicability to the inversion of magnetotelluric data is also mathematically verified.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2015, 25, 3; 483-498
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A hybrid algorithm for solving inverse problems in elasticity
    Autorzy:
    Barabasz, B.
    Gajda-Zagórska, E.
    Migórski, S.
    Paszyński, M.
    Schaefer, R.
    Smołka, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/331427.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    inverse problem
    hierarchic genetic strategy
    hybrid optimization
    automatic hp adaptive finite element method
    zagadnienie odwrotne
    strategia genetyczna
    optymalizacja hybrydowa
    metoda elementów skończonych
    Opis:
    The paper offers a new approach to handling difficult parametric inverse problems in elasticity and thermo-elasticity, formulated as global optimization ones. The proposed strategy is composed of two phases. In the first, global phase, the stochastic hp-HGS algorithm recognizes the basins of attraction of various objective minima. In the second phase, the local objective minimizers are closer approached by steepest descent processes executed singly in each basin of attraction. The proposed complex strategy is especially dedicated to ill-posed problems with multimodal objective functionals. The strategy offers comparatively low computational and memory costs resulting from a double-adaptive technique in both forward and inverse problem domains. We provide a result on the Lipschitz continuity of the objective functional composed of the elastic energy and the boundary displacement misfits with respect to the unknown constitutive parameters. It allows common scaling of the accuracy of solving forward and inverse problems, which is the core of the introduced double-adaptive technique. The capability of the proposed method of finding multiple solutions is illustrated by a computational example which consists in restoring all feasible Young modulus distributions minimizing an objective functional in a 3D domain of a photo polymer template obtained during step and flash imprint lithography.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 4; 865-886
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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