MCDM (version 1.0)

MetaRanking: Implementation of MetaRanking function for Multi-Criteria Decision Making Problems.

Description

The MetaRanking function internally calls functions MMOORA, TOPSIS, VIKOR and WASPAS and then calculates a sum of the their rankings.

Usage

MetaRanking(decision, weights, cb, lambda, v)

Arguments

decision

The decision matrix (m x n) with the values of the m alternatives, for the n criteria.

weights

A vector of length n, containing the weights for the criteria. The sum of the weights has to be 1.

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.

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.

Value

MetaRanking returns a data frame which contains the rankings of the Multi-MOORA, TOPSIS, VIKOR, WASPAS Methods and the MetaRanking of the alternatives.

Examples

d <- matrix(rpois(12, 5), nrow = 4)
 w <- c(0.2, 0.2, 0.6)
 cb <- c('max','min','max')
 lambda <- 0.5
 v <- 0.5
 MetaRanking(d,w,cb,lambda,v)