# 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

 `1` ```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

 ``` 1 2 3 4 5 6 7 8 9 10``` ``` 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 29, 2017, 9:42 a.m.