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    Wyświetlanie 1-4 z 4
    Tytuł:
    Hyper-heuristics for cross-domain search
    Autorzy:
    Cichowicz, T..
    Drozdowski, M.
    Frankiewicz, M.
    Pawlak, G.
    Rytwinski, F.
    Wasilewski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/201681.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    hyper-heuristics
    cross-domain heuristic search
    HyFlex
    Opis:
    In this paper we present two hyper-heuristics developed for the Cross-Domain Heuristic Search Challenge. Hyper-heuristics solve hard combinatorial problems by guiding low level heuristics, rather than by manipulating problem solutions directly. Two hyper-heuristics are presented: Five Phase Approach and Genetic Hive. Development paths of the algorithms and testing methods are outlined. Performance of both methods is studied. Useful and interesting experience gained in construction of the hyper-heuristics are presented. Conclusions and recommendations for the future advancement of hyper-heuristic methodologies are discussed.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 4; 801-808
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Scheduling trucks in a multi-door cross-docking system with time windows
    Autorzy:
    Ozden, G.
    Saricicek, I.
    Powiązania:
    https://bibliotekanauki.pl/articles/200989.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    multi-door cross-docking center
    time window
    logistics
    decision support system
    meta-heuristics
    wielodrzwiowe centrum przeładunkowe
    okno czasowe
    Logistyka
    system wspomagania decyzji
    metaheurystyka
    Opis:
    Cross-docking is a strategy that distributes products directly from a supplier or manufacturing plant to a customer or retail chain, reducing handling or storage time. This study focuses on the truck scheduling problem, which consists of assigning each truck to a door at the dock and determining the sequences for the trucks at each door considering the time-window aspect. The study presents a mathematical model for door assignment and truck scheduling with time windows at multi-door cross-docking centers. The objective of the model is to minimize the overall earliness and tardiness for outbound trucks. Simulated annealing (SA) and tabu search (TS) algorithms are proposed to solve largesized problems. The results of the mathematical model and of meta-heuristic algorithms are compared by generating test problems for different sizes. A decision support system (DSS) is also designed for the truck scheduling problem for multi-door cross-docking centers. Computational results show that TS and SA algorithms are efficient in solving large-sized problems in a reasonable time.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 2; 344-362
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Algorithms solving the Internet shopping optimization problem with price discounts
    Autorzy:
    Musial, J.
    Pecero, J. E.
    Lopez-Loces, M. C.
    Fraire-Huacuja, H. J.
    Bouvry, P.
    Blazewicz, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/200209.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    e-commerce
    Internet shopping
    applications of operations research
    approximations
    algorithms
    heuristics
    combinatorial optimization
    zakupy przez Internet
    wnioski z badań operacyjnych
    aproksymacje
    algorytmy
    heurystyki
    optymalizacja kombinatoryczna
    Opis:
    The Internet shopping optimization problem arises when a customer aims to purchase a list of goods from a set of web-stores with a minimum total cost. This problem is NP-hard in the strong sense. We are interested in solving the Internet shopping optimization problem with additional delivery costs associated to the web-stores where the goods are bought. It is of interest to extend the model including price discounts of goods. The aim of this paper is to present a set of optimization algorithms to solve the problem. Our purpose is to find a compromise solution between computational time and results close to the optimum value. The performance of the set of algorithms is evaluated through simulations using real world data collected from 32 web-stores. The quality of the results provided by the set of algorithms is compared to the optimal solutions for small-size instances of the problem. The optimization algorithms are also evaluated regarding scalability when the size of the instances increases. The set of results revealed that the algorithms are able to compute good quality solutions close to the optimum in a reasonable time with very good scalability demonstrating their practicability.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 3; 505-516
    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 1-4 z 4

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