Módszerek összehasonlítása

	Maclaurin-szimmetrikus középérték operátor	Bonferroni-féle középérték (BM)	Az ideális megoldáshoz való hasonlóságon alapuló preferenciarendezési technika
Tudományterület	Döntéshozatal	Döntéshozatal	Döntéshozatal
Módszercsalád	MCDM	MCDM	MCDM
Keletkezés éve	2014	1950	1981
Megalkotó	Variants developed from Maclaurin's mathematical theory	Bonferroni, C.	Hwang, C. L., Yoon, K.
Típus	Symmetric mean aggregation operator for multiple criteria	Interrelationship-based aggregation — captures pairwise interactions	Distance-based (compromise)
Alapmű	Qin, J., Liu, X., & Pedrycz, W. (2014). An extended TOPSIS model for multiple attribute decision making with interval-valued intuitionistic fuzzy information. International Journal of Fuzzy Systems, 16(1), 99-113.	Bonferroni, C. (1950). Sulle medie multiple di potenze. Bollettino dell'Unione Matematica Italiana	Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications — A State-of-the-Art Survey. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag
Alternatív nevek	MSM, Maclaurin Mean	—	—
Kapcsolódó	3	0	8
Összefoglaló	The Maclaurin Symmetric Mean (MSM) operator is an aggregation method that combines multiple criteria or attribute values using symmetric mean functions. Unlike simple averaging, MSM captures interactions between criteria and enables flexible sensitivity to criterion magnitudes through a parameter λ. It is particularly useful in fuzzy multi-criteria decision analysis and handles both individual and joint effects of criteria.	BONFERRONI-MEAN (Bonferroni Mean (BM)) is a aggregation multi-criteria decision-making (MCDM) method introduced by Bonferroni, C. in 1950. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.