FuzzyMMOORA: Implementation of Fuzzy MULTIMOORA Method for Multi-Criteria...

In FuzzyMCDM: Multi-Criteria Decision Making Methods for Fuzzy Data

Description

The FuzzyMMOORA function implements both the Fuzzy Multi-Objetive Optimization by Ration Analysis (MOORA) and the Fuzzy "Full Multiplicative Form" (Fuzzy MULTIMOORA).

Usage

FuzzyMMOORA(decision, weights, cb)

Arguments

decision	The decision matrix (m x (n*3)) with the values of the m alternatives, for the n criteria, and multiplied by 3 since they are triangular fuzzy numbers.
weights	A vector of length n*3, containing the fuzzy weights for the criteria.
cb	A vector of length n. Each component is either cb(i)='max' if the i-th criterion is benefit or cb(i)='min' if the i-th criterion is a cost.

Value

FuzzyMMOORA returns a data frame which contains the scores and the four rankings calculated (Ratio System, Reference Point, Multiplicative Form and Multi-MOORA ranking).

References

Balezentis, T. and Balezentis, A. A Survey on Development and Applications of the Multi-criteria Decision Making Method MULTIMOORA. Journal of Multi-Criteria Decision Analysis, 21(3-4), 209-222, 2014.

Examples

 d <- matrix(c(0.63,0.42,0.63,0.67,0.8,0.59,0.8,0.84,0.92,0.75,0.92,0.92,0.29,0.71,0.75,
 0.42,0.46,0.88,0.92,0.59,0.63,1,1,0.71,0.75,0.59,0.42,0.42,0.92,0.75,0.58,0.59,1,0.88,
 0.76,0.75,0.59,0.71,0.42,0.33,0.75,0.88,0.58,0.51,0.88,0.96,0.71,0.67,0.5,0.67,0.67,
 0.67,0.67,0.84,0.84,0.84,0.84,0.92,0.96,0.96,0.67,0.54,0.54,0.25,0.84,0.71,0.71,0.42,
 0.96,0.88,0.88,0.59,0.67,0.71,0.42,0.25,0.84,0.88,0.59,0.42,0.96,0.96,0.75,0.58,0.54,
 0.625,0.625,0.295,0.705,0.79,0.795,0.46,0.88,0.92,0.875,0.62),nrow=4,ncol=24)
 w <- c(1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24,
 1/24,1/24,1/24,1/24,1/24,1/24,1/24,1/24)
 cb <- c('max','max','max','max','max','max','max','max')
 FuzzyMMOORA(d,w,cb)

FuzzyMCDM documentation built on May 1, 2019, 7:20 p.m.