Measuring the metallurgical supply chain resilience using fuzzy analytic network process
P. Wicher
; VŠB – Technical University of Ostrava, Czech Republic
F. Zapletal
; VŠB – Technical University of Ostrava, Czech Republic
R. Lenort
; VŠB – Technical University of Ostrava, Czech Republic
D. Staš
; ŠKODA AUTO University, Czech Republic
APA 6th Edition Wicher, P., Zapletal, F., Lenort, R. i Staš, D. (2016). Measuring the metallurgical supply chain resilience using fuzzy analytic network process. Metalurgija, 55 (4), 783-786. Preuzeto s https://hrcak.srce.hr/157453
MLA 8th Edition Wicher, P., et al. "Measuring the metallurgical supply chain resilience using fuzzy analytic network process." Metalurgija, vol. 55, br. 4, 2016, str. 783-786. https://hrcak.srce.hr/157453. Citirano 05.12.2019.
Chicago 17th Edition Wicher, P., F. Zapletal, R. Lenort i D. Staš. "Measuring the metallurgical supply chain resilience using fuzzy analytic network process." Metalurgija 55, br. 4 (2016): 783-786. https://hrcak.srce.hr/157453
Harvard Wicher, P., et al. (2016). 'Measuring the metallurgical supply chain resilience using fuzzy analytic network process', Metalurgija, 55(4), str. 783-786. Preuzeto s: https://hrcak.srce.hr/157453 (Datum pristupa: 05.12.2019.)
Vancouver Wicher P, Zapletal F, Lenort R, Staš D. Measuring the metallurgical supply chain resilience using fuzzy analytic network process. Metalurgija [Internet]. 2016 [pristupljeno 05.12.2019.];55(4):783-786. Dostupno na: https://hrcak.srce.hr/157453
IEEE P. Wicher, F. Zapletal, R. Lenort i D. Staš, "Measuring the metallurgical supply chain resilience using fuzzy analytic network process", Metalurgija, vol.55, br. 4, str. 783-786, 2016. [Online]. Dostupno na: https://hrcak.srce.hr/157453. [Citirano: 05.12.2019.]
Sažetak The article presents a methodology for measuring the metallurgical supply chain resilience, which enables the ascertainment of key resilience capabilities and measurable criteria, and determining a level of the resilience. The methodology is based on Analytic Network Process (ANP), which is used to solve the complex decision-making problems, whose structures can be mapped as non-linear networks. Since ambiguous pairwise comparisons expressed by fuzzy sets are considered, the Fuzzy Analytic Network Process (FANP) is applied. The methodology is verified on the generalised model of a metallurgical supply chain. The SuperDecisions software was used for the application. The experiments performed demonstrate the high level of suitability of the FANP approach for measuring metallurgical supply chain resilience.