Purpose Making techniques PROMETHEE, direction of research in this emerging field. Design/Methodology/Approach: literature related to MCDM techniques PROMETHEE, ELECTRE, VIKOR and TOPSIS. Literature has been segregated to understand various issues and work related to MCDM techniques PROMETHEE, ELECTRE, VIKOR and TOPSIS. A detailed review is used to sort out the literature and develop the resear...

Most decision making problems can be considered as multiple criteria decision making (MCDM) problems, and should be solved by MCDM method. The main advantage of MCDM is that it can give managers many dimensions to consider related elements, and evaluate all possible options under variable degrees. This paper applied fuzzy set theory and a compromised MCDM method VIKOR method to evaluate the ser...

The topic of this paper are discrete decision problems with multiple criteria. We rst deene discrete multiple criteria decision problems and introduce a classiication scheme for multiple criteria optimization problems. To do so we use multiple criteria optimization classes. The main result is a characterization of the class of lexicographic max-ordering problems by two very useful properties, r...

Multi criterion Decision Making (MCDM) methods are widely applied in many domains for finding rank based on the available conflicting nature of the criteria and to choose the best alternative. MCDM methods comprise of complex mathematical calculations which required time to solve, especially, when number of criteria and alternatives are more. In order to automate the process software is require...

A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the f...

Single-objective to multi-objective/many-objective optimization (SMO) is a new paradigm in the evolutionary transfer (ETO), since there are only “1 + 4” pioneering works on SMOs so far, that is, “1” continuous and firstly performed by Professors L. Feng H.D. Wang, “4” proposed our group for discrete cases. As computational paradigm, theoretical insights into relatively rare now. Therefore, we p...