New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance

Autor: Mikael Collan, Mario Fedrizzi, Pasi Luukka
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Advances in Fuzzy Systems, Vol 2015 (2015)
Druh dokumentu: article
ISSN: 1687-7101
1687-711X
DOI: 10.1155/2015/251646
Popis: This paper introduces new closeness coefficients for fuzzy similarity based TOPSIS. The new closeness coefficients are based on multidistance or fuzzy entropy, are able to take into consideration the level of similarity between analysed criteria, and can be used to account for the consistency or homogeneity of, for example, performance measuring criteria. The commonly known OWA operator is used in the aggregation process over the fuzzy similarity values. A range of orness values is considered in creating a fuzzy overall ranking for each object, after which the fuzzy rankings are ordered to find a final linear ranking. The presented method is numerically applied to a research and development project selection problem and the effect of using two new closeness coefficients based on multidistance and fuzzy entropy is numerically illustrated.
Databáze: Directory of Open Access Journals
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