Pregled bibliografske jedinice broj: 1217566
Modelling transport activities from inventory replenishments in supply chains by use of numerical simulations and machine learning algorithms
Modelling transport activities from inventory replenishments in supply chains by use of numerical simulations and machine learning algorithms // Proceedings of the 5th Logistics International Conference [LOGIC 2022] / Vidović, Milorad (ur.).
Beograd: Saobraćajni fakultet Univerziteta u Beogradu, 2022. str. 76-87 doi:10.37528/FTTE/9788673954530.LO (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1217566 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Modelling transport activities from inventory
replenishments in supply chains by use of
numerical simulations and machine learning
algorithms
Autori
Žic, Samir ; Žic, Jasmina
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 5th Logistics International Conference [LOGIC 2022]
/ Vidović, Milorad - Beograd : Saobraćajni fakultet Univerziteta u Beogradu, 2022, 76-87
ISBN
978-86-7395-453-0
Skup
5th Logistics International Conference (LOGIC 2022)
Mjesto i datum
Beograd, Srbija, 26.05.2022. - 27.05.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
supply chain management, periodic review, inventories, logistics, symbolic regression
Sažetak
A periodic review inventory policy represents a standard inventory management model in modern supply chains due to its many advantages. This paper studies its logistic aspects coming from the number and size of transport activities related to inventory replenishments resulting from normally distributed market demand. Due to the stochastic nature of market demand, no simple procedures or algorithms for determining the optimal values of the characteristic variables of the periodic review inventory policy exists, so extensive numerical simulations and symbolic regression analysis of a supply chain echelon are used in this paper. Equations for average order size and required number of orders related to inventory replenishments are developed with R2 Goodness of Fit and Correlation Coefficient higher than 0.99 tested on 139.500 simulation experiments of a supply chain.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo, Temeljne tehničke znanosti
POVEZANOST RADA
Ustanove:
Tehnički fakultet, Rijeka,
Fakultet strojarstva i brodogradnje, Zagreb
