A Comparative Analysis of TOPSIS & VIKOR Methods in the Selection of Industrial Robots

Abstract

Now-a-days robots are very essential in manufacturing industries for the optimization of their production. So selection of an industrial robot for a particular application is one of the most vital problems in real time manufacturing environment. The decision maker needs to choose the most suitable and applicable industrial robot in order to get the required output with minimum cost and having the specific abilities. This paper mainly focuses to compare the different multiple criteria decision making (MCDM) methods such as TOPSIS and VIKOR Method for selection of alternative industrial robots. Both the methods are based on an aggregating function that represents closeness to the ideal solution. VIKOR method is based on linear normalization whereas TOPSIS method used vector normalization to eliminate the units of criterion functions. A solution obtained by TOPSIS method has the shortest distance from the ideal one and farthest from the negative ideal solution. VIKOR method helps to determine a compromise solution that gives a maximum group utility for the majority and minimum for opponents.