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    Wyświetlanie 1-6 z 6
    Tytuł:
    Problem-Independent Approach to Multiprocessor Dependent Task Scheduling
    Autorzy:
    Król, D.
    Zydek, D.
    Koszałka, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/226364.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    tasks scheduling
    DAG
    genetic algorithm
    tabu search
    makespan
    Opis:
    This paper concerns Directed Acyclic Graph task scheduling on parallel executors. The problem is solved using two new implementations of Tabu Search and genetic algorithm presented in the paper. A new approach to solution coding is also introduced and implemented in both metaheuristics algorithms. Results given by the algorithms are compared to those generated by greedy LPT and SS-FF algorithms; and HAR algorithm. The analysis of the obtained results of multistage simulation experiments confirms the conclusion that the proposed and implemented algorithms are characterized by very good performance and characteristics.
    Źródło:
    International Journal of Electronics and Telecommunications; 2012, 58, 4; 369-379
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Two meta-heuristic algorithms for scheduling on unrelated machines with the late work criterion
    Autorzy:
    Wang, Wen
    Chen, Xin
    Musial, Jędrzej
    Blazewicz, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/330022.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    late work minimization
    unrelated machines
    tabu search
    genetic algorithm
    minimalizacja opóźnienia
    przeszukiwanie tabu
    algorytm genetyczny
    Opis:
    A scheduling problem in considered on unrelated machines with the goal of total late work minimization, in which the late work of a job means the late units executed after its due date. Due to the NP-hardness of the problem, we propose two meta-heuristic algorithms to solve it, namely, a tabu search (TS) and a genetic algorithm (GA), both of which are equipped with the techniques of initialization, iteration, as well as termination. The performances of the designed algorithms are verified through computational experiments, where we show that the GA can produce better solutions but with a higher time consumption. Moreover, we also analyze the influence of problem parameters on the performances of these metaheuristics.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2020, 30, 3; 573-584
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Heuristic algorithms for joint optimization of unicast and anycast traffic in elastic optical network-based large-scale computing systems
    Autorzy:
    Markowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330713.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    elastic optical network
    joint optimization
    distributed data center
    metaheuristic algorithm
    tabu search
    elastyczna sieć optyczna
    optymalizacja wspólna
    baza danych rozproszona
    algorytm heurystyczny
    metoda tabu search
    Opis:
    In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2017, 27, 3; 605-622
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Automatic parametric fault detection in complex analog systems based on a method of minimum node selection
    Autorzy:
    Bilski, A.
    Wojciechowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/330761.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    complex analog system
    support vector machine (SVM)
    tabu search
    genetic algorithm
    parametric fault detection
    system analogowy
    maszyna wektorów wspierających
    metoda tabu search
    algorytm genetyczny
    detekcja uszkodzeń
    Opis:
    The aim of this paper is to introduce a strategy to find a minimal set of test nodes for diagnostics of complex analog systems with single parametric faults using the support vector machine (SVM) classifier as a fault locator. The results of diagnostics of a video amplifier and a low-pass filter using tabu search along with genetic algorithms (GAs) as node selectors in conjunction with the SVM fault classifier are presented. General principles of the diagnostic procedure are first introduced, and then the proposed approach is discussed in detail. Diagnostic results confirm the usefulness of the method and its computational requirements. Conclusions on its wider applicability are provided as well.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 3; 655-668
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Research on optimization of unrelated parallel machine scheduling based on IG-TS algorithm
    Autorzy:
    Chi, Xinfu
    Liu, Shijing
    Li, Ce
    Powiązania:
    https://bibliotekanauki.pl/articles/2173693.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    warp knitting machine
    parallel machine scheduling
    iterative greedy algorithm
    tabu search
    osnowarka
    planowanie maszyn równoległych
    algorytm zachłanny iteracyjny
    przeszukiwanie tabu
    Opis:
    This issue is a typical NP-hard problem for an unrelated parallel machine scheduling problem with makespan minimization as the goal and no sequence-related preparation time. Based on the idea of tabu search (TS), this paper improves the iterative greedy algorithm (IG) and proposes an IG-TS algorithm with deconstruction, reconstruction, and neighborhood search operations as the main optimization process. This algorithm has the characteristics of the strong capability of global search and fast speed of convergence. The warp knitting workshop scheduling problem in the textile industry, which has the complex characteristics of a large scale, nonlinearity, uncertainty, and strong coupling, is a typical unrelated parallel machine scheduling problem. The IG-TS algorithm is applied to solve it, and three commonly used scheduling algorithms are set as a comparison, namely the GA-TS algorithm, ABC-TS algorithm, and PSO-TS algorithm. The outcome shows that the scheduling results of the IG-TS algorithm have the shortest manufacturing time and good robustness. In addition, the production comparison between the IG-TS algorithm scheduling scheme and the artificial experience scheduling scheme for the small-scale example problem shows that the IG-TS algorithm scheduling is slightly superior to the artificial experience scheduling in both planning and actual production. Experiments show that the IG-TS algorithm is feasible in warp knitting workshop scheduling problems, effectively realizing the reduction of energy and the increase in efficiency of a digital workshop in the textile industry.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 4; art. no. e141724
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Solving scheduling problems with integrated online sustainability observation using heuristic optimization
    Autorzy:
    Burduk, Anna
    Musiał, Kamil
    Balashov, Artem
    Batako, Andre
    Safonyk, Andrii
    Powiązania:
    https://bibliotekanauki.pl/articles/2173719.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    production scheduling
    sustainable development
    genetic algorithm
    meta-heuristics
    intelligent optimization methods of production systems
    tabu search
    harmonogramowanie produkcji
    zrównoważony rozwój
    algorytm genetyczny
    przeszukiwanie tabu
    metaheurystyki
    inteligentne metody optymalizacji systemów produkcyjnych
    Opis:
    The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143830
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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