Measuring the metallurgical supply chain resilience using fuzzy analytic network process
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Croatian Metallurgical Society
2016-10-01
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| Series: | Metalurgija |
| Subjects: | |
| Online Access: | http://hrcak.srce.hr/file/232042 |
| _version_ | 1828415238204030976 |
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| author | P. Wicher F. Zapletal R. Lenort D. Staš |
| author_facet | P. Wicher F. Zapletal R. Lenort D. Staš |
| author_sort | P. Wicher |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T13:42:31Z |
| format | Article |
| id | doaj.art-74d5c6e3efb2416094e84a9b11d8e0c1 |
| institution | Directory Open Access Journal |
| issn | 0543-5846 1334-2576 |
| language | English |
| last_indexed | 2024-12-10T13:42:31Z |
| publishDate | 2016-10-01 |
| publisher | Croatian Metallurgical Society |
| record_format | Article |
| series | Metalurgija |
| spelling | doaj.art-74d5c6e3efb2416094e84a9b11d8e0c12022-12-22T01:46:39ZengCroatian Metallurgical SocietyMetalurgija0543-58461334-25762016-10-01554783786Measuring the metallurgical supply chain resilience using fuzzy analytic network processP. WicherF. ZapletalR. LenortD. StašThe 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.http://hrcak.srce.hr/file/232042metallurgymethodologysupply chain resilienceAnalytic Network Processfuzzy sets |
| spellingShingle | P. Wicher F. Zapletal R. Lenort D. Staš Measuring the metallurgical supply chain resilience using fuzzy analytic network process Metalurgija metallurgy methodology supply chain resilience Analytic Network Process fuzzy sets |
| title | Measuring the metallurgical supply chain resilience using fuzzy analytic network process |
| title_full | Measuring the metallurgical supply chain resilience using fuzzy analytic network process |
| title_fullStr | Measuring the metallurgical supply chain resilience using fuzzy analytic network process |
| title_full_unstemmed | Measuring the metallurgical supply chain resilience using fuzzy analytic network process |
| title_short | Measuring the metallurgical supply chain resilience using fuzzy analytic network process |
| title_sort | measuring the metallurgical supply chain resilience using fuzzy analytic network process |
| topic | metallurgy methodology supply chain resilience Analytic Network Process fuzzy sets |
| url | http://hrcak.srce.hr/file/232042 |
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