Title: Information fusion method on hexagonal fuzzy number-based multi-criteria decision-making problems

Authors: V. Lakshmana Gomathi Nayagam; R. Bharanidharan

Addresses: Department of Mathematics (DST-FIST Sponsored), National Institute of Technology, Tiruchirappalli, 620015, Tamilnadu, India ' Department of Mathematics (DST-FIST Sponsored), National Institute of Technology, Tiruchirappalli, 620015, Tamilnadu, India

Abstract: Receiving information from experts is a crucial stage in fuzzy multi-criteria decision-making (MCDM) problems. Various types of fuzzy numbers are used in fuzzy MCDM problems. In particular, hexagonal fuzzy number is widely used in fuzzy MCDM problems because of its convenience on piecewise linearity. The major drawback of fuzzy MCDM problems is non-availability of information for some alternatives with respect to some criteria while collecting information from the experts. To overcome this, researchers found some methodologies which are known as information fusion/infusion methods. In this paper, we have proposed two infusion methods based on score function and similarity measure. We have analysed the proposed infusion algorithms by giving illustrative numerical examples. Further, due to the needfulness, a new similarity measure on hexagonal fuzzy numbers have been introduced and used in the infusion method.

Keywords: hexagonal fuzzy numbers; information fusion; missing data MCDM; similarity measure on HXFN.

DOI: 10.1504/IJRIS.2026.152163

International Journal of Reasoning-based Intelligent Systems, 2026 Vol.18 No.2, pp.72 - 85

Received: 03 Jul 2023
Accepted: 05 Aug 2024
Published online: 10 Mar 2026 *

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