Volume 55, Number 5, September-October 2021
|Page(s)||2657 - 2683|
|Published online||20 September 2021|
A novel extension of TOPSIS with interval type-2 trapezoidal neutrosophic numbers using (α, β, γ)-cuts
Department of Basic Sciences, University of Engineering and Technology, Taxila, Pakistan
2 Institute of IR 4.0, The National University of Malaysia, 43600 Bangi, Selangor, Malaysia
3 Department of Mathematics, Near East University, TRNC Mersin 10, Nicosia, Turkey
4 Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey
* Corresponding author: email@example.com
Accepted: 9 August 2021
Multi-criteria decision-making (MCDM) is concerned with structuring and solving decision problems involving multiple criteria for decision-makers in vague and inadequate environment. The “Technique for Order Preference by Similarity to Ideal Solution’’ (TOPSIS) is one of the mainly used tactic to deal with MCDM setbacks. In this article, we put forward an extension of TOPSIS with interval type-2 trapezoidal neutrosophic numbers (IT2TrNNs) using the concept of (α, β, γ)-cut. First, we present a novel approach to compute the distance between two IT2TrNNs using ordered weighted averaging (OWA) operator and (α, β, γ)-cut. Subsequently, we broaden the TOPSIS method in the context of IT2TrNNs and implemented it on a MCDM problem. Lastly, a constructive demonstration and several contrasts with the other prevailing techniques are employed to articulate the practicability of the proposed technique. The presented strategy yields a flexible solution for MCDM problems by considering the attitudes and perspectives of the decision-makers.
Mathematics Subject Classification: 06Dxx / 06D72
Key words: Multi-criteria decision making (MCDM) / interval type-2 trapezoidal neutrosophic number (IT2TrNN) / ordered weighted averaging (OWA) operator
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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