Experimental analysis of humanistic systems in decision making

Abstract

Computational techniques for generating intuitionistic fuzzy random numbers (IFRNs) for the formulation of test problems in the management of humanistic systems have been developed and implemented. The research was conducted to address the limited scope of the method and agent architecture for the generation of intuitionistic fuzzy numbers. Intuitionistic fuzzy variable is amenable to human decision processes, and an agent architecture was transformed into a MATLAB program and implemented to generate any required IFRNs, which were applied to solve multi-attributes decision making (MADM) problems for humanistic systems using the principles of Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). The inadequacy of using a single metric function in the method was also illustrated. Numerical experiments were performed to analyse the contradiction rate of the hamming and euclidean distances.

Keywords: Intuitionistic fuzzy random numbers, Pseudorandom numbers, MADM, TOPSIS, Linguistic variable