Сравнение на методи

	Оператор на симетричното средно на Maclaurin	Средна стойност на Бонферони (BM)	Степенувана средна стойност (средна на Хьолдер)
Област	Вземане на решения	Вземане на решения	Вземане на решения
Семейство	MCDM	MCDM	MCDM
Година на възникване	2014	1950	1934
Създател	Variants developed from Maclaurin's mathematical theory	Bonferroni, C.	Hardy, G. H. Littlewood, J. E. Pólya, G.
Тип	Symmetric mean aggregation operator for multiple criteria	Interrelationship-based aggregation — captures pairwise interactions	Power mean family — parametric generalisation of WAM/WGM/WHM
Основополагащ източник	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	Hardy, G. H., Littlewood, J. E., Pólya, G. (1934). Inequalities. Cambridge University Press ISBN: 978-0-521-35880-4
Други названия	MSM, Maclaurin Mean	—	—
Свързани	3	0	0
Резюме	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.	POWER-MEAN (Weighted Power Mean (Hölder Mean)) is a aggregation multi-criteria decision-making (MCDM) method introduced by Hardy, G. H. Littlewood, J. E. Pólya, G. in 1934. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.