Decision-Making using the Hesitant Fuzzy Sets COMET Method : an Empirical Study of the Electric City Buses Selection

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Tytuł
Decision-Making using the Hesitant Fuzzy Sets COMET Method
Podtytuł
an Empirical Study of the Electric City Buses Selection
Odpowiedzialność
Wojciech Sałabun, Artur Karczmarczyk, Jarosław Wątróbski
Twórcy
Punktacja publikacji
Osoba Dysc. Pc k m P U Pu Opis
0000-0002-4415-9414 5.6 20 1 3 11,55 0,5774 11,5480 aut. roz.
Gł. język publikacji
Angielski (English)
Data publikacji
2018
Objętość
8 (stron).
Szacowana objętość
0,5 (arkuszy wydawniczych)
Identyfikator DOI
10.1109/SSCI.2018.8628864
Adres URL
https://ieeexplore.ieee.org/document/8628864
Cechy publikacji
  • Publikacja konferencyjna

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  • Publikacja konferencyjna
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Słowa kluczowe
Dokument źródłowy
IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI) ; 8th IEEE Symposium Series on Computational Intelligence (IEEE SSCI) NOV 18-21, 2018 Bengaluru, INDIA : proceedings paper / Edited by:Sundaram, S.. - Bengaluru, INDIA : [br.w, 2018
Strony: 1485-1492
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Data zgłoszenia do bazy Publi
2019-02-26
PBN
Wyświetl
WorkId
21292

Abstrakt

en

The analysis of decisions under uncertainty has always been a challenging problem and numerous tools have been proposed to deal with it. Recently, a new extension of the COMET method has been proposed, which is based on hesitant fuzzy sets (HFS). This approach has been presented to handle situations in which experts hesitate during identifying the membership grade for the considered attributes. This technique, as well as its basic version, are entirely free of the rank reversal phenomenon, which allows making more reliable decisions.In this paper, we present a short empirical case study of the electric city buses selection. This problem allows presenting how the decision-making process is working by using the HFS COMET. Afterwards, the paper shows efficiency and advantages of the HFS COMET in accordance to the presented study case. The obtained results show that the HFS COMET is a chance to get more reliable decisions when uncertain data is being used.

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