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    Wyświetlanie 1-7 z 7
    Tytuł:
    Algorytm pszczeli w optymalizacji modelu przepływowego szeregowania zadań
    Bees algorithm in optimization of task scheduling for flow shop model
    Autorzy:
    Popielarski, Wiesław
    Powiązania:
    https://bibliotekanauki.pl/articles/41204031.pdf
    Data publikacji:
    2010
    Wydawca:
    Uniwersytet Kazimierza Wielkiego w Bydgoszczy
    Tematy:
    algorytm pszczół
    model przepływowy
    szeregowanie zadań
    bees algorithm
    flow shop
    task scheduling
    Opis:
    Problem optymalizacji przy ograniczonych zasobach jest jednym z podstawowych tematów w informatyce. Algorytm pszczeli z szerszej grupy algorytmów stadnych, wynaleziony i przedstawiony w połowie ostatniej dekady, wydaje się być obiecującym narzędziem w optymalizacji kombinatorycznej. Artykuł przedstawia wyniki badań nad algorytmem w optymalizacji modelu przepływowego szeregowania zadań i zakreśla dalsze ich obszary.
    Problem of optimization with limited resources is fundamental one in computer sciences. The bees algorithm from wider group of swarm algorithms, invented and implemented about 2005, seems to be a good candidate for next useful tool for combinatorial optimization. Article presents the results of the bees algorithm research in flow shop model of task scheduling and outlines areas of further exploration
    Źródło:
    Studia i Materiały Informatyki Stosowanej; 2010, 2; 47-50
    1689-6300
    Pojawia się w:
    Studia i Materiały Informatyki Stosowanej
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A comparison of nature inspired algorithms for the quadratic assignment problem
    Autorzy:
    Chmiel, W.
    Kadłuczka, P.
    Kwiecień, J.
    Filipowicz, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/202135.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    permutation problem
    quadratic assignment problem
    ant algorithm
    bees algorithm
    problem permutacji
    problem przydziału kwadratowego
    algorytm Ant Colony
    algorytm pszczół
    Opis:
    This paper presents an application of the ant algorithm and bees algorithm in optimization of QAP problem as an example of NP-hard optimization problem. The experiments with two types of algorithms: the bees algorithm and the ant algorithm were performed for the test instances of the quadratic assignment problem from QAPLIB, designed by Burkard, Karisch and Rendl. On the basis of the experiments results, an influence of particular elements of algorithms, including neighbourhood size and neighbourhood search method, will be determined.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2017, 65, 4; 513-522
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Comparison of different approaches in traffic forecasting models for the D-200 highway in Turkey
    Autorzy:
    Dogan, E.
    Korkmaz, E.
    Akgungor, A. P.
    Powiązania:
    https://bibliotekanauki.pl/articles/196318.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
    Tematy:
    traffic forecasting
    SARIMA
    differential evolution algorithm
    artificial bee colony algorithm
    prognozowanie ruchu
    algorytm ewolucji różnicowej
    algorytm sztucznej kolonii pszczół
    Opis:
    Short-term traffic estimations have a significant influence in terms of effectively controlling vehicle traffic. In this study, short-term traffic forecasting models have been developed based on different approaches. Seasonal autoregressive integrated moving average (SARIMA), artificial bee colony (ABC) and differential evolution (DE) algorithms are the techniques used in the optimization of models, which have been developed by using observation data for the D-200 highway in Turkey. 80% of the data were used for training, with the remaining data used for testing. The performances of the models were illustrated with mean absolute errors (MAEs), mean absolute percentage errors (MAPEs), the coefficient of determination (R2) and the root-mean-square errors (RMSEs). It is understood that all the models provided consistent and useful results when the developed models were compared with the statistical results. In the models created separately for two lanes, the R2 values of the models were calculated to be approximately 92% for the right lane, which is generally used by heavy vehicles, and 88% for the left lane, which is used by less traffic. Based on the MAE and RMSE values, the model developed by the ABC algorithm gave the lowest error and showed more effective performance than the other approaches. Thus, the ABC model showed that it is appropriate for use on other highways in Turkey.
    Źródło:
    Zeszyty Naukowe. Transport / Politechnika Śląska; 2018, 99; 25-42
    0209-3324
    2450-1549
    Pojawia się w:
    Zeszyty Naukowe. Transport / Politechnika Śląska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Zastosowanie algorytmów rojowych do optymalizacji parametrów w modelach układów regulacji
    Application of swarm intelligence algorithms to optimization of control system models
    Autorzy:
    Tomera, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/269153.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
    Tematy:
    algorytmy rojowe
    optymalizacja parametrów
    algorytm mrówkowy
    algorytm sztucznej kolonii pszczół
    algorytm optymalizacji rojem cząstek
    swarm intelligence
    swarm based optimization
    ant colony optimization
    Artificial Bee Colony
    particle swarm optimization (PSO)
    Opis:
    W pracy przedstawione zostały algorytmy rojowe, takie jak: algorytm mrówkowy, zmodyfikowany algorytm mrówkowy, algorytm sztucznej kolonii pszczół oraz algorytm optymalizacji rojem cząstek. Dla tych algorytmów przygotowane zostało oprogramowanie w Matlabie, pozwalające na optymalizację parametrów poszukiwanych modeli matematycznych, wyznaczanych na podstawie przeprowadzonych testów identyfikacyjnych lub na optymalizację parametrów regulatorów zastosowanych w modelach matematycznych układów sterowania.
    The paper presents the swarm intelligence algorithms, such as: ant colony algorithm (ACO), the modified ant colony algorithm (MACO), the artificial bee colony algorithm (ABC) and the particle swarm optimization algorithm (PSO). Ant colony optimization (ACO) based upon the observation of the behavior of ant colonies looking for food in the surrounding anthill. Feeding ants it is based on finding the shortest path transitions between a food source and the anthill. In the process of foraging ants on their paths crossing from the nest to a food source and back, they leave a pheromone trail. The work presents also the modified ant colony algorithm (MACO). This algorithm is based on searching the solution space surrounded by the best solution obtained in the previous iteration. If you find a local minimum, the proposed algorithm uses pheromone to find a new solution space, while retaining the position information current local minimum. The artificial bee colony algorithm is one of the well-known swarm intelligence algorithms. In the past decade there has been created several different algorithms based on the observation of the behavior of cooperative bees. Among them, the most frequently analyzed and used is bee algorithm proposed in 2005 by Dervis Karaboga and was be used in the proposed paper. The particle swarm optimization algorithm (PSO) is based on adjusting the change speed of the moving particles to a speed of particles movement in the neighborhood. Particle optimization algorithm is one of the computational techniques derived on the basis of swarm behavior such as flocks of birds and schools of fish, which is the basis for the functioning of the exchange of information to enable them to cooperate. It was noticed that the animals in the herd tend to maintain the optimum distance from their neighbors, by appropriate adjustment of their speed. This method allows the synchronous and collision-free motion, often accompanied by sudden changes of direction and due to the rearrangement of the optimal formation. For these algorithms has been prepared the software in Matlab, allowing to optimization of the mathematical models designated on the basis of the carried out identification tests and control parameters used in the mathematical model of the control system.
    Źródło:
    Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2015, 46; 97-102
    1425-5766
    2353-1290
    Pojawia się w:
    Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online parameter identification of SPMSM based on improved artificial bee colony algorithm
    Autorzy:
    Wu, Chunli
    Jiang, Shuai
    Bian, Chunyuan
    Powiązania:
    https://bibliotekanauki.pl/articles/1955171.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony algorithm
    Euclidean distance
    online identification
    parameter identification
    urface-mounted permanent magnet synchronous motor
    algorytm sztucznej kolonii pszczół
    odległość euklidesowa
    identyfikacja online
    identyfikacja parametrów
    silnik synchroniczny z magnesami trwałymi montowany na powierzchni czołowej
    Opis:
    The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.
    Źródło:
    Archives of Electrical Engineering; 2021, 70, 4; 777-790
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Nonlinear PID controller parameter optimization using modified hybrid artificial bee colony algorithm for continuous stirred tank reactor
    Autorzy:
    Pugazhenthi, Nedumal
    Selvaperumal, S.
    Vijayakumar, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/2128163.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony
    stirred tank reactor
    genetic algorithm
    nonlinear PID
    controller performance measures
    sztuczna kolonia pszczół
    reaktor zbiornikowy z mieszadłem
    algorytm genetyczny
    PID nieliniowy
    miernik wydajności kontrolera
    Opis:
    The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137348, 1--10
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Nonlinear PID controller parameter optimization using modified hybrid artificial bee colony algorithm for continuous stirred tank reactor
    Autorzy:
    Pugazhenthi, Nedumal
    Selvaperumal, S.
    Vijayakumar, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/2173628.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony
    stirred tank reactor
    genetic algorithm
    nonlinear PID
    controller performance measures
    sztuczna kolonia pszczół
    reaktor zbiornikowy z mieszadłem
    algorytm genetyczny
    PID nieliniowy
    miernik wydajności kontrolera
    Opis:
    The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137348
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-7 z 7

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