An Empirical Comparison of TOPSIS and VIKOR for Ranking Decision-Making Models

Abstract

Multi-criteria decision making (MCDM) comes under operational research whose sole purpose is to compare, rank, and select several alternatives for multiple and conflicting criteria. Several MCDM methods have been used by decision-makers to choose one alternative among several decision-making models that met their goals, objectives, desire, and values. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) are two prevailing MCDM methods built upon an aggregating function that represents proximity to the optimal solution. In TOPSIS vector normalization and in VIKOR linear scale normalization is used to transform all criteria into a uniform range. The VIKOR method provides a compromise solution based on maximum group utility and minimum individual regret. TOPSIS elects a solution that is farther from the negative ideal solution and closer to the ideal solution. In this paper, a correlative inquiry of these two methods is demonstrated with an analytical case study producing their similar and distinct features.