Comparison and Analysis of Fuzzy Methods—TOPSIS, COPRAS-G, ANP, ELECTRE and AHP Using MATLAB

Fuzzy logic is a multi-valued logic which is obtained from fuzzy set theory. It deals with human resourcing which is approximate than ‘very unlikely’, when compared to the traditional binary sets the truth value ranges in degree between 0 and 1. The main concept of fuzzy logic is that it provides a practical way of approach to automate the complex data analysis, fusion and inference processes which is usually performed by human experts with extensive experiences. COPRAS-G and COPRAS (Venkatesan et al. in Performance analysis of mobile agent failure recovery in e-service applications 32(1–2):38–43, 2005, Licata in Employing fuzzy logic in the diagnosis of a clinical case, 2010) decision-making methods are separately used in various applications to illustrate the approximate evaluation of attributes. This helps in selecting the best thing. It can be used to select best websites, company, project manager, etc. It can also be used to select the location for constructing warehouse, underground dam, etc. We propose the case study to compare both COPRAS and COPRAS-G (Aruldoss et al. in A survey on multi criteria decision making methods and its applications, 2013, Dhavachelvan et al. in A new approach in development of distributed framework for automated software testing using agents, 2006) decision making fuzzy methods for finding the rate of diseases occurring to children, teenagers and old aged people. That is, what are the diseases may occur at certain age can be accurately predicted through this project. Two methods Simplified COPRAS and COPRAS-G are implemented with the same input to obtain the best and the worst alternative. The ranking of the Simplified COPRAS-G and COPRAS method are compared by the parameters. Each parameter is applied in both the method in order to find the better method.