Description Usage Arguments Value Examples

The `MetaRanking`

function internally calls functions `FuzzyMMOORA`

, `FuzzyTOPSISLinear`

, `FuzzyTOPSISVector`

, `FuzzyVIKOR`

and `FuzzyWASPAS`

and then calculates a sum of the their rankings and an aggregated ranking by applying the `RankAggreg`

package.

1 | ```
MetaRanking(decision, weights, cb, lambda, v)
``` |

`decision` |
The decision matrix ( |

`weights` |
A vector of length |

`cb` |
A vector of length |

`lambda` |
A value in [0,1]. It is used in the calculation of the W index for WASPAS method. |

`v` |
A value in [0,1]. It is used in the calculation of the Q index for VIKOR method. |

`MetaRanking`

returns a data frame which contains the rankings of the Fuzzy Multi-MOORA, Fuzzy TOPSIS (linear transformation and vectorial normalization), Fuzzy VIKOR, Fuzzy WASPAS Methods and the MetaRankings of the alternatives.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
d <- matrix(c(0.68,0.4,0.6,0.2,0.4,1.44,0.67,0.9,0.45,0.6,2.2,
0.95,1.2,0.7,0.8,18,8,8,25,6,21,11.5,11.5,32.5,9,24,15,15,40,
12,9,0.66,0.66,0,0,10,2.33,2.33,0.66,0.33,10,4.33,4.33,2.33,
1.66,5,1.33,1.33,5.66,1,7,3,3,7.66,2,8.66,5,5,9.33,3.66,2.33,
0.66,0.33,1.33,1.66,4.33,2,1.33,3,2.66,6.33,3.66,3,5,4.33),
nrow=5,ncol=15)
w <- c(0.189,0.214,0.243,0.397,0.432,0.462,0.065,0.078,0.096,
0.068,0.084,0.106,0.174,0.190,0.207)
cb <- c('min','max','max','min','min')
lambda <- 0.5
v <- 0.5
MetaRanking(d,w,cb,lambda,v)
``` |

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