An Interval Type-2 Fuzzy Likelihood-Based MABAC Approach and Its Application in Selecting Hotels on a Tourism Website
International Journal of Fuzzy SystemsPublished 11 July 2016
Sumin Yu, Jing Wang, Jian‐qiang Wang, Jian‐qiang Wang, Jian‐qiang Wang
Citations165
SJR quartileQ2
SJR score0.71
SNIP1.01
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TL;DR
A new multi-attributive border approximation area comparison (MABAC) approach to solve multi-criteria decision-making (MCDM) problems based on the likelihood of interval type-2 fuzzy numbers (IT2FNs).
Abstract
As an extension of type-1 fuzzy sets (T1FSs), interval type-2 fuzzy sets (IT2FSs) can be used to model both extrinsic and intrinsic uncertainties. Based on the likelihood of interval type-2 fuzzy numbers (IT2FNs), this paper proposes a new multi-attributive border approximation area comparison (MABAC) approach to solve multi-criteria decision-making (MCDM) problems. First, an algorithm to decompose IT2FNs into the embedded type-1 fuzzy numbers (T1FNs) is proposed. Second, based on the closeness degree of T1FNs, the likelihood of IT2FNs is defined using the decomposition algorithm, and related properties are discussed. Third, the total ranking of alternatives is obtained using the MABAC approach based on the likelihood of IT2FNs. Finally, a practical example of selecting hotels from a tourism website is presented to verify the validity and feasibility of the proposed approach. A comparative analysis with existing methods is also described.
Keywords
Computer ScienceDecision SciencesMathematics
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