Linguistic Intuitionistic Fuzzy VIKOR Method with the Application of Artificial Neural Network - John Robinson Peter Dawson; Leonishiya Arockia Selvaraj (Engineering Proceedings)
This paper proposes Linguistic Intuitionistic Fuzzy (LIF) aggregation operators, LIF-energies, LIF-correlation, and LIF-correlation coefficients. Supporting theorems are also proven for the proposed functions, which are utilized in the Linguistic Intuitionistic Fuzzy–Vlse Kriterijumska Optimizacija Kompromisno Resenje (LIF-VIKOR) method within Decision Support Systems (DSS). Additionally, numerical examples are presented to validate the method. The sensitivity analysis of weighting vectors is conducted, and the consistency of final rankings affirms the robustness of the proposed approaches. Arithmetic operations, specifically subtraction and division, are applied to LIF numbers (LIFNs) within the LIF-VIKOR algorithm. Furthermore, a function called the Linguistic Median Membership (LMM) function is introduced to convert LIFN values into crisp numbers. In the LIF-VIKOR algorithm, the proposed correlation coefficient is used for ranking alternatives, while the entropy method is applied to compute weights. Sensitivity analysis is performed to ensure the consistency of the proposed method. Finally, an Artificial Neural Network (ANN) is integrated into the VIKOR algorithm to enhance computational efficiency, reducing the time and manpower required to solve the model.