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PAVLAS, M. ŠOMPLÁK, R. SMEJKALOVÁ, V. NEVRLÝ, V. SZÁSZIOVÁ, L. KŮDELA, J. POPELA, P.
Originální název
Spatially distributed production data for supply chain models - Forecasting with hazardous waste
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
This paper introduces a novel approach to forecasting future commodity production in hundreds of nodes, which represents a key input for many applications of supply-chain models. A mathematical model was proposed to handle the problem of forecasting with spatially distributed and uncertain data. It is derived from the principle of regression analysis and extended by a data reconciliation technique. Additional areal constraints guarantee mass conservation in a tree-like structure, which reflects the organisational arrangement of an investigated region. The proposed model was tested through a case study, where future production of hazardous waste suitable for thermal treatment was forecasted in 206 base-nodes, 14 superior nodes and one apex. Based on an extensive investigation of historical data, it was revealed that extrapolations carried out at different levels of the hierarchical organisational structure lead to inconsistent forecasts. The differences between forecasts reached up to 50%. In addition to this, mass conservation was violated. Significant corrections were performed by computations utilising the formulated model. The corrections ranged from between 0% and 12% for 90% of nodes. There were 17 nodes, where massive adjustments of up to 30% were inevitable.
Klíčová slova
Supply chain; forecasting; extrapolation; short time series; hazardous waste; thermal treatment
Autoři
PAVLAS, M.; ŠOMPLÁK, R.; SMEJKALOVÁ, V.; NEVRLÝ, V.; SZÁSZIOVÁ, L.; KŮDELA, J.; POPELA, P.
Vydáno
14. 7. 2017
Nakladatel
Elsevier Ltd
Místo
UK
ISSN
0959-6526
Periodikum
Journal of Cleaner Production
Číslo
161
Stát
Spojené království Velké Británie a Severního Irska
Strany od
1317
Strany do
1328
Strany počet
11
BibTex
@article{BUT138002, author="Martin {Pavlas} and Radovan {Šomplák} and Veronika {Smejkalová} and Vlastimír {Nevrlý} and Lenka {Szásziová} and Jakub {Kůdela} and Pavel {Popela}", title="Spatially distributed production data for supply chain models - Forecasting with hazardous waste", journal="Journal of Cleaner Production", year="2017", number="161", pages="1317--1328", doi="10.1016/j.jclepro.2017.06.107", issn="0959-6526" }