A Comparison of Various Normalization in Techniques for Order Performance by Similarity to Ideal Solution (TOPSIS)

The core of Operation Research is the development of approaches for optional Decision Making. A prominent class of such problem is Multi-Criteria Decision Making MCDM. MCDM is used when different alternatives and different criteria are applied to make better Decision Making. There are several methodologies available in MCDM out which TOPSIS is one of the traditional methods in use. The TOPSIS Method is used to identify solution from a finite set of alternatives based upon simultaneous minimization of distance from a nadir point. In the first step of TOPSIS the vector normalization is performed. In our proposed work different normalization techniques are applied to find the best normalization which suits the TOPSIS Method. It is evaluated based on the performance measures like time and space complexity.