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

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 hom...

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Main Authors: Mikael Collan, Mario Fedrizzi, Pasi Luukka
Format: Article
Language:English
Published: Wiley 2015-01-01
Series:Advances in Fuzzy Systems
Online Access:http://dx.doi.org/10.1155/2015/251646
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author Mikael Collan
Mario Fedrizzi
Pasi Luukka
author_facet Mikael Collan
Mario Fedrizzi
Pasi Luukka
author_sort Mikael Collan
collection DOAJ
description 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.
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issn 1687-7101
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publishDate 2015-01-01
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spelling doaj-art-bbdf225a5fd14af4858734781193ba642025-08-20T03:22:54ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2015-01-01201510.1155/2015/251646251646New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and MultidistanceMikael Collan0Mario Fedrizzi1Pasi Luukka2School of Business and Management, Lappeenranta University of Technology, P.O. Box 20, 53851 Lappeenranta, FinlandDepartment of Industrial Engineering, University of Trento, Via Mesiano 77, 38123 Trento, ItalySchool of Business and Management, Lappeenranta University of Technology, P.O. Box 20, 53851 Lappeenranta, FinlandThis 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.http://dx.doi.org/10.1155/2015/251646
spellingShingle Mikael Collan
Mario Fedrizzi
Pasi Luukka
New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance
Advances in Fuzzy Systems
title New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance
title_full New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance
title_fullStr New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance
title_full_unstemmed New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance
title_short New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance
title_sort new closeness coefficients for fuzzy similarity based fuzzy topsis an approach combining fuzzy entropy and multidistance
url http://dx.doi.org/10.1155/2015/251646
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AT mariofedrizzi newclosenesscoefficientsforfuzzysimilaritybasedfuzzytopsisanapproachcombiningfuzzyentropyandmultidistance
AT pasiluukka newclosenesscoefficientsforfuzzysimilaritybasedfuzzytopsisanapproachcombiningfuzzyentropyandmultidistance