Mathematics and Computational Sciences

An integrated eigenvalue based neural network approach for MAGDM with intuitionistic Fuzzy sets

Document Type : Original Article

Authors

Gopal Sumithra 1
John Robinson P 1
Wilson Arul Prakash S 2

1 Department of Mathematics, Bishop Heber College, Affiliated to Bharathidasan University, Tiruchirappalli-620017.

2 Department of Mathematics, Jeppiaar College of Arts & Science, Affiliated to University of Madras, Chennai-603103.

https://doi.org/10.30511/mcs.2025.2075323.1541
Abstract
This paper addresses Multi-Criteria Group Decision Making (MCGDM), also known as Multiple Attribute Group Decision Making (MAGDM), under the framework of intuitionistic fuzzy sets. To solve fuzzy linear algebraic equations, linear space techniques involving real eigenvalues are employed. These solutions are then used to determine decision-maker weights in MAGDM problems. During the weight determination process, multiple criteria are explicitly incorporated, and several results obtained through the proposed methods are normalized. Additionally, decision-maker weights for attributes, along with corresponding decision-making approaches, are introduced. Furthermore, Artificial Neural Network (ANN) techniques are applied to enhance the determination of decision-maker weights. The feasibility and effectiveness of the proposed approach are demonstrated through numerical examples. The convergence curve shows stable error reduction without underfitting or overfitting, validating the robustness of the proposed ANN framework for reliable application in intuitionistic fuzzy set–based MAGDM.

Keywords

MAGDM
Eigen value
Intuitionistic Fuzzy sets
Weight vector
ANN

Subjects

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Mathematics and Computational Sciences
Volume 7, Issue 1
Winter 2026
Pages 84-103

  • Receive Date 20 October 2025
  • Revise Date 03 December 2025
  • Accept Date 04 December 2025

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