Modification of the Best–Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers
| Autor: | Dragan Pamučar, Goran Ćirović, Ivan Petrović |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Structure (mathematical logic)
0209 industrial biotechnology Basis (linear algebra) Fuzzy set General Engineering Stability (learning theory) 02 engineering and technology Extension (predicate logic) computer.software_genre Fuzzy logic Computer Science Applications 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining Sensitivity (control systems) computer Selection (genetic algorithm) Mathematics |
| Zdroj: | Expert Systems with Applications. 91:89-106 |
| ISSN: | 0957-4174 |
| DOI: | 10.1016/j.eswa.2017.08.042 |
| Popis: | This paper presents a new approach for the treatment of uncertainty which is based on interval-valued fuzzy-rough numbers (IVFRN). It is shown that by integrating the rough approach with the traditional fuzzy approach, the subjectivity that exists when defining the borders of fuzzy sets is eliminated. IVFRN make decision making possible using only the internal knowledge in the operative data available to the decision makers. In this way objective uncertainties are used and there is no need to rely on models of assumptions. Instead of different external parameters in the application of IVFRN, the structure of the given data is used. On this basis an original multi-criteria model was developed based on an IVFRN approach. In this multi-criteria model the traditional steps of the BWM (Best–Worst method) and MABAC (Multi-Attributive Border Approximation area Comparison) methods are modified. The model was tested and validated on a study of the optimal selection of fire fighting helicopters. Testing demonstrated that the model based on IVFRN enabled more objective expert evaluation of the criteria in comparison with traditional fuzzy and rough approaches. A sensitivity analysis of the IVFRN BWM-MABAC model was carried out by means of 57 scenarios, the results of which showed a high degree of stability. The results of the IVFRN model were validated by comparing them with the results of the fuzzy and rough extension of the MABAC, COPRAS and VIKOR models. |
| Databáze: | OpenAIRE |
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