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Preliminary communication

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

Fulltext: english, pdf (228 KB) pages 783-786 downloads: 389* cite
APA 6th Edition
Wicher, P., Zapletal, F., Lenort, R. & Staš, D. (2016). Measuring the metallurgical supply chain resilience using fuzzy analytic network process. Metalurgija, 55 (4), 783-786. Retrieved from 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, no. 4, 2016, pp. 783-786. https://hrcak.srce.hr/157453. Accessed 29 Mar. 2020.
Chicago 17th Edition
Wicher, P., F. Zapletal, R. Lenort and D. Staš. "Measuring the metallurgical supply chain resilience using fuzzy analytic network process." Metalurgija 55, no. 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), pp. 783-786. Available at: https://hrcak.srce.hr/157453 (Accessed 29 March 2020)
Vancouver
Wicher P, Zapletal F, Lenort R, Staš D. Measuring the metallurgical supply chain resilience using fuzzy analytic network process. Metalurgija [Internet]. 2016 [cited 2020 March 29];55(4):783-786. Available from: https://hrcak.srce.hr/157453
IEEE
P. Wicher, F. Zapletal, R. Lenort and D. Staš, "Measuring the metallurgical supply chain resilience using fuzzy analytic network process", Metalurgija, vol.55, no. 4, pp. 783-786, 2016. [Online]. Available: https://hrcak.srce.hr/157453. [Accessed: 29 March 2020]

Abstracts
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.

Keywords
metallurgy; methodology; supply chain resilience; Analytic Network Process; fuzzy sets

Hrčak ID: 157453

URI
https://hrcak.srce.hr/157453

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