Against Artificial Complexification: Crisp vs. Fuzzy Information in the TOPSIS Method

DOI

10.2991/asum.k.210827.046How to use a DOI?

Keywords

decision making, TOPSIS, fuzzy sets, information representation

Abstract

The question of whether the use of crisp or fuzzy input information in the TOPSIS method produces a different ranking is explored. Using a basic representation of fuzziness through triangular fuzzy numbers, a set of randomly generated fuzzy and crisp multicriteria decision problems are solved. Then, the corresponding rankings are compared and variations in the top alternative are studied. The results show that changes in the top alternative are minor. This situation, coupled with the fact that the “true” ranking is unknown and that more complex models of “fuzzy” information require a huge amount of precise information from the decision maker side, raise the discussion of whether in this specific context a “complexification” of the input data makes sense.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - David A. Pelta
AU  - María T. Lamata
AU  - José L. Verdegay
AU  - Carlos Cruz
AU  - Ana Salas
PY  - 2021
DA  - 2021/08/30
TI  - Against Artificial Complexification: Crisp vs. Fuzzy Information in the TOPSIS Method
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 345
EP  - 351
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.046
DO  - 10.2991/asum.k.210827.046
ID  - Pelta2021
ER  -