Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "szeregowanie zadań" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-4 z 4
    Tytuł:
    Reducing the mast vibration of single-mast stacker cranes by gain-scheduled control
    Autorzy:
    Hajdu, S.
    Gáspár, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/331336.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    robust control
    LPV systems
    gain scheduling
    stacker cranes
    sterowanie odporne
    szeregowanie zadań
    układnica
    Opis:
    In the frame structure of stacker cranes harmful mast vibrations may appear due to the inertial forces of acceleration or the braking movement phase. This effect may reduce the stability and positioning accuracy of these machines. Unfortunately, their dynamic properties also vary with the lifted load magnitude and position. The purpose of the paper is to present a controller design method which can handle the effect of a varying lifted load magnitude and position in a dynamic model and at the same time reveals good reference signal tracking and mast vibration reducing properties. A controller design case study is presented step by step from dynamic modeling through to the validation of the resulting controller. In the paper the dynamic modeling possibilities of single-mast stacker cranes are summarized. The handling of varying dynamical behavior is realized via the polytopic LPV modeling approach. Based on this modeling technique, a gain-scheduled controller design method is proposed, which is suitable for achieving the goals set. Finally, controller validation is presented by means of time domain simulations.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 4; 791-802
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Scheduling preemptable jobs on identical processors under varying availability of an additional continuous resource
    Autorzy:
    Różycki, R.
    Waligóra, G.
    Węglarz, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/330888.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    machine scheduling
    preemptable jobs
    continuous resource
    makespan
    mathematical programming
    szeregowanie zadań
    zasób ciągły
    programowanie matematyczne
    Opis:
    In this work we consider a problem of scheduling preemptable, independent jobs, characterized by the fact that their processing speeds depend on the amounts of a continuous, renewable resource allocated to jobs at a time. Jobs are scheduled on parallel, identical machines, with the criterion of minimization of the schedule length. Since two categories of resources occur in the problem: discrete (set of machines) and continuous, it is generally called a discrete-continuous scheduling problem. The model studied in this paper allows the total available amount of the continuous resource to vary over time, which is a practically important generalization that has not been considered yet for discrete-continuous scheduling problems. For this model we give some properties of optimal schedules on a basis of which we propose a general methodology for solving the considered class of problems. The methodology uses a two-phase approach in which, firstly, an assignment of machines to jobs is defined and, secondly, for this assignment an optimal continuous resource allocation is found by solving an appropriate mathematical programming problem. In the approach various cases are considered, following from assumptions made on the form of the processing speed functions of jobs. For each case an iterative algorithm is designed, leading to an optimal solution in a finite number of steps.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 3; 693-706
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Lower bounds for the scheduling problem with uncertain demands
    Autorzy:
    Berkoune, D.
    Mesghouni, K.
    Rabenasolo, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/908409.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    szeregowanie zadań
    prognozowanie popytu
    granica dolna
    flexible job shop scheduling
    insertion
    makespan
    predicted demands
    lower bounds
    Opis:
    This paper proposes various lower bounds to the makespan of the flexible job shop scheduling problem (FJSP). The FJSP is known in the literature as one of the most difficult combinatorial optimisation problems (NP-hard). We will use genetic algorithms for the optimisation of this type of problems. The list of the demands is divided in two sets: the actual demand, which is considered as certain (a list of jobs with known characteristics), and the predicted demand, which is a list of uncertain jobs. The actual demand is scheduled in priority by the genetic algorithm. Then, the predicted demand is inserted using various methods in order to generate different scheduling solutions. Two lower bounds are given for the makespan before and after the insertion of the predicted demand. The performance of solutions is evaluated by comparing the real values obtained on many static and dynamic scheduling examples with the corresponding lower bounds.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 2; 263-269
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A hybrid scheduler for many task computing in big data systems
    Autorzy:
    Vasiliu, L.
    Pop, F.
    Negru, C.
    Mocanu, M.
    Cristea, V.
    Kolodziej, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/907647.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    many task computing
    scheduling heuristics
    QoS
    big data system
    simulation
    obliczenia wielofunkcyjne
    szeregowanie zadań
    duży zbiór danych
    Opis:
    With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or even exabytes scale. Such huge data sets need data-intensive computing applications and impose performance requirements to the infrastructures that support them, such as high scalability, storage, fault tolerance but also efficient scheduling algorithms. This paper focuses on providing a hybrid scheduling algorithm for many task computing that addresses big data environments with few penalties, taking into consideration the deadlines and satisfying a data dependent task model. The hybrid solution consists of several heuristics and algorithms (min-min, min-max and earliest deadline first) combined in order to provide a scheduling algorithm that matches our problem. The experimental results are conducted by simulation and prove that the proposed hybrid algorithm behaves very well in terms of meeting deadlines.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2017, 27, 2; 385-399
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies