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Wyszukujesz frazę "logistics center" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Research on the site selection and path layout of the logistics distribution center of marine ships based on a mathematical model
Autorzy:
Tong, Haolin
Powiązania:
https://bibliotekanauki.pl/articles/2173920.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
marine ships
distribution center
site selection
ship logistics
mathematical model
statki morskie
centrum dystrybucyjne
wybór lokalizacji
logistyka statków
model matematyczny
Opis:
For logistics enterprises, site selection and path layout are related to the cost and efficiency of distribution, which is a very critical issue and has an important impact on the development of enterprises. Compared with land logistics, the cost of marine ship logistics is higher due to the high cost of ships, so the research on the location and path layout of its distribution centers is also particularly important. This paper established a two-layer model under the assumption that unit transpor-tation costs and administration expenses are known for the site selection and path layout problems of marine ship logistics distribution centers. Corresponding constraint conditions were set. The upper layer was the optimization model of the site selection problem of the distribution center, and the objective function was to minimize operating and construction costs and was solved using the quantum particle swarm optimization (QPSO) algorithm. The lower layer was the optimization model of the distribution path layout, and the objective function was to minimize the logistics distribution cost and was solved using the ant colony optimization (ACO) algorithm. The model was verified through an example analysis. It was assumed that there were three ships, five candidate distribution centers, and ten customer points. The model was solved in MATLAB software. The results of the example analysis showed that compared with K-means, genetic algorithm (GA), and particle swarm optimization (PSO)-ACO algorithms, the QPSO-ACO algorithm had the shortest running time, about 60 s, which saved about 50% compared to the K-means algorithm. The optimal cost of the QPSO-ACO algorithm was 293,400 yuan, which was significantly lower than the K-means, GA, and PSO-ACO algorithms (459,600 yuan, 398,300 yuan, and 357,700 yuan). In this example, the site obtained by the QPSO-ACO algorithm was distribution center 2, and the obtained path distribution was 1-7-5-4, 2-6-3, and 10-8-9. The results verify the effectiveness of the QPSO-ACO algorithm in solving the problem of site selection and path layout. The QPSO-ACO algorithm can be applied in the actual marine ship logistics.
Źródło:
Archives of Transport; 2022, 63, 3; 23--34
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
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
    Wyświetlanie 1-2 z 2

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