PMID- 34178177
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230306
IS  - 1868-5137 (Print)
IS  - 1868-5145 (Electronic)
VI  - 14
IP  - 3
DP  - 2023
TI  - Multicriteria decision making approach using an efficient novel similarity 
      measure for generalized trapezoidal fuzzy numbers.
PG  - 1507-1529
LID - 10.1007/s12652-021-03347-x [doi]
AB  - Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one 
      suitable alternative among a pool of alternatives governed by predefined multiple 
      criteria. Some of the factors like imprecision, lack of information/data, etc., 
      which are present in traditional MCDM processes have showcased their lack of 
      efficiency and hence eventually it has paved the ways for the development of 
      Fuzzy multicriteria decision making (FMCDM). In FMCDM processes, the decision 
      makers can model most of the real-life phenomena by fuzzy information-based 
      preferences. The availability of a wide literature on similarity measure (SM) 
      emphasizes the vital role of SM of generalized fuzzy numbers (GFNs) to conduct 
      accurate and precise decision making in FMCDM problems. Despite having few 
      advantages, most of the existing approaches possessed a certain degree of counter 
      intuitiveness and discrepancies. Thus, we have attempted to propose a novel SM 
      for generalized trapezoidal fuzzy numbers (GTrFNs) which could deliberately 
      overcome the impediments associated with the earlier existing approaches. 
      Moreover, a meticulous comparative study with the existing approaches is also 
      presented. This paper provides us with an improved method to obtain the 
      similarity values between GTrFNs and the proposed SM consists of calculating the 
      prominent features of fuzzy numbers such as expected value and variance. We use 
      fourteen different sets of GTrFNs, to compare the fruition of the present 
      approach with the existing SM approaches. Furthermore, to show the utility and 
      applicability of our proposed measure, we illustrate few practical scenarios such 
      as the launching of an electronic gadget by a company, a problem of medical 
      diagnosis and finally, a proper anti-virus mask selection in light of the recent 
      COVID-19 pandemic. The obtained results with our proposed SM, for the mentioned 
      FMCDM problems, are analytically correct and they depict the efficiency and 
      novelty of the present article.
CI  - (c) The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of 
      Springer Nature 2021.
FAU - Dutta, Palash
AU  - Dutta P
AUID- ORCID: 0000-0002-1565-4889
AD  - Department of Mathematics, Dibrugarh University, Dibrugarh, Assam 786004 India. 
      GRID: grid.412023.6. ISNI: 0000 0001 0674 667X
FAU - Borah, Gourangajit
AU  - Borah G
AD  - Department of Mathematics, Dibrugarh University, Dibrugarh, Assam 786004 India. 
      GRID: grid.412023.6. ISNI: 0000 0001 0674 667X
LA  - eng
PT  - Journal Article
DEP - 20210617
PL  - Germany
TA  - J Ambient Intell Humaniz Comput
JT  - Journal of ambient intelligence and humanized computing
JID - 101538212
PMC - PMC8211316
OTO - NOTNLM
OT  - Generalized trapezoidal fuzzy numbers
OT  - Multicriteria decision making
OT  - Similarity measure
OT  - Uncertainty/vagueness
COIS- Conflict of interestAuthors declare that they have no conflict of interest.
EDAT- 2021/06/29 06:00
MHDA- 2021/06/29 06:01
PMCR- 2021/06/17
CRDT- 2021/06/28 05:58
PHST- 2020/09/07 00:00 [received]
PHST- 2021/06/08 00:00 [accepted]
PHST- 2021/06/29 06:00 [pubmed]
PHST- 2021/06/29 06:01 [medline]
PHST- 2021/06/28 05:58 [entrez]
PHST- 2021/06/17 00:00 [pmc-release]
AID - 3347 [pii]
AID - 10.1007/s12652-021-03347-x [doi]
PST - ppublish
SO  - J Ambient Intell Humaniz Comput. 2023;14(3):1507-1529. doi: 
      10.1007/s12652-021-03347-x. Epub 2021 Jun 17.