Bandingkan kaedah

	Operator Purata Simetri Maclaurin	Bonferroni Mean (BM)	Teknik untuk Susunan Keutamaan mengikut Keserupaan dengan Penyelesaian Ideal
Bidang	Pembuatan Keputusan	Pembuatan Keputusan	Pembuatan Keputusan
Keluarga	MCDM	MCDM	MCDM
Tahun asal	2014	1950	1981
Pengasas	Variants developed from Maclaurin's mathematical theory	Bonferroni, C.	Hwang, C. L., Yoon, K.
Jenis	Symmetric mean aggregation operator for multiple criteria	Interrelationship-based aggregation — captures pairwise interactions	Distance-based (compromise)
Sumber perintis	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
Alias	MSM, Maclaurin Mean	—	—
Berkaitan	3	0	8
Ringkasan	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.