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Wyszukujesz frazę "heuristic problems" wg kryterium: Wszystkie pola


Wyświetlanie 1-2 z 2
Tytuł:
Heuristic algorithms applied to the problems of servicing actors in supply chains
Autorzy:
Izdebski, M.
Jacyna-Gołda, I.
Markowska, K.
Murawski, J.
Powiązania:
https://bibliotekanauki.pl/articles/224087.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
supply chain
genetic algorithm
ant algorithm
łańcuchy dostaw
algorytm genetyczny
algorytm mrówkowy
Opis:
The paper discusses main decision problems analysed in the subject matter of servicing actors operating in the supply chains, i.e. the vehicle routing problem, vehicles-to-task assignment problem and the problem of entities’ localization in the supply chain. The input data used to describe supply chains is given as well as the basic constraints and the criterion functions used in the development of mathematical models describing the supply chains. Servicing actors in supply chains is the complex decision making problem. Operators in the supply chains are constrained by: production capacity of the suppliers, the demand of the customers in particular working days, storage capacities of warehouses, handling capacities of warehouses, suppliers’ and warehouses’ time windows and other. The efficiency of supply chain is described by cost of transport between operators, costs of passing cargoes through warehouses and delivery time to the recipient. The heuristic algorithms, like genetic and ant algorithms are detailed and used to identify issues related to the operation of actors operating in the supply chains are described. These algorithms are used for solving localization problems in supply chains, vehicle routing problems, and assignment problems. The complexity of presented issues (TSP is known as NP-hard problem) limits the use of precise algorithms and implies the need to use heuristic algorithms. It should be noted that solutions generated by these algorithms for complex decision instances are sub-optimal solutions, but nonetheless it is accepted from the practical point of view.
Źródło:
Archives of Transport; 2017, 44, 4; 25-34
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
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 1-2 z 2

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