Crisp vs. Fuzzy Data in Multicriteria Decision Making: The Case of the VIKOR Method

Ceballos, Blanca; Lamata, María Teresa; Pelta, David A.; Yager, Ronald R.

doi:10.1007/978-3-319-66830-7_41

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Based on these aggregated values, the alternatives are then ranked from a most preferred to a least preferred (Krishnan et al, 2017 ). Although a wide range of MCDM techniques is available, it is interesting to note that the core input for all these techniques is the decision matrix that encapsulates the data values of alternatives across the decision criteria (Ceballos et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Past efforts in determining suitable normalization methods for multi-criteria decision-making: A short survey

Krishnan

2022

Front. Big Data

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The use of a multi-criteria decision-making (MCDM) technique mostly begins with normalizing the incommensurable data values in the decision matrix. Numerous normalization methods are available in the literature and applying different normalization methods to an MCDM technique is proven to deliver varying results. As such, selecting suitable normalization methods for an MCDM technique has emerged as an intriguing research topic, especially with the advent of big data. Several efforts have been made to compare the suitability of various normalization methods, but regrettably, no paper provides an updated review of these crucial efforts. This study, therefore, aimed to trace articles reporting such efforts and review them based on the following three perspectives: (1) the normalization methods considered, (2) the MCDM methods considered, and (3) the comparison metrics used to determine the suitable normalization methods. The relevant articles were extracted with the aid of Google Scholar using the keywords of “normalization” and “MCDM,” and Tableau software was used to analyze further the data gathered through the articles. A total of five limitations were uncovered based on the current state of literature, and potential future works to address those limitations were offered. This paper is the first to compile and review the previous investigations that compared and determined the ideal normalization methods for an MCDM technique.

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Section: Introductionmentioning

confidence: 99%

Past efforts in determining suitable normalization methods for multi-criteria decision-making: A short survey

Krishnan

2022

Front. Big Data

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“…In a previous research [4] we explore a similar situation using a different MCDM method (VIKOR) in a very basic setting. The main finding was that the rankings have not too much differences.…”

Section: Introductionmentioning

confidence: 99%

“…the left/right values in the triangular fuzzy numbers) in the input data have any impact in the potential rankings' discrepancies (these factors were not taken into account in [4]). In order to shed light into this topic, we design and perform a simulation based experiment to assess such impact.…”

Section: Introductionmentioning

confidence: 99%

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

Pelta¹,

Lamata²,

Verdegay³

et al. 2021

Atlantis Studies in Uncertainty Modelling

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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.

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Application of Fuzzy Analytical Hierarchy Process (FAHP) for Selecting the Suitable Hydraulic Fracturing Method in Oil Recovery Enhancement

2018

International Journal of Petroleum and Petrochemical Engineerin

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Crisp vs. Fuzzy Data in Multicriteria Decision Making: The Case of the VIKOR Method

Cited by 3 publications

References 7 publications

Past efforts in determining suitable normalization methods for multi-criteria decision-making: A short survey

Past efforts in determining suitable normalization methods for multi-criteria decision-making: A short survey

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

Application of Fuzzy Analytical Hierarchy Process (FAHP) for Selecting the Suitable Hydraulic Fracturing Method in Oil Recovery Enhancement

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