Multiple-criteria decision analysis
Nary TOPSIS is multi-criteria decision making method, which is built to take into consideration also preference over positive or negative ideal solution. It was developed in 2020. Original TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) is based on the idea of forming two ideal solutions (best possible case and worst possible case) and comparing the current alternative to these two. Several researchers have pointed out that one downside of the method is that in original TOPSIS ranking index is irrespective of the weights of the decision-maker assigns to these two separations. In Nary TOPSIS preference is executed by posing weaker or stricter conditions to norm operators in creation of ideal vectors. Justification for replacing minimum and maximum in positive and negative ideal solution computation is quite intuitive. The standard fuzzy intersection (minimum) is the weakest fuzzy intersection and hence producing largest set from among those produced by all possible fuzzy intersections (T-norms). Similarly standard fuzzy union (maximum) is the strongest fuzzy union and hence it produces the smallest set among the sets produced by all possible fuzzy unions (T-conorms). Now by changing the norm operator we can also address relative importantess type of a problem in TOPSIS at the point where we are creating Positive and Negative ideal solutions. This is obviously done separately for positive ideal solution and negative ideal solution. (Wikipedia).
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