FuzzyTOPSISLinear: Implementation of Fuzzy TOPSIS Method for Multi-Criteria...

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

Description

The FuzzyTOPSISLinear function implements the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) Method with de linear transformation (maximum) as normalization method.

Usage

FuzzyTOPSISLinear(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

FuzzyTOPSISLinear returns a data frame which contains the score of the R index and the ranking of the alternatives.

References

Chen, C.T. Extensions of the TOPSIS for group decision-manking under fuzzy environment. Fuzzy Sets and Systems, 114, 1-9, 2000.

Examples

 d <- matrix(c(5.7,6.3,6.3,7.7,8.3,8,9.3,9.7,9,5,9,7,7,10,9,9,10,10,5.7,8.3,7,7.7,9.7,9,
 9,10,10,8.33,9,7,9.67,10,9,10,10,10,3,7,6.3,5,9,8.3,7,10,9.7),nrow=3,ncol=15)
 w <- c(0.7,0.9,1,0.9,1,1,0.77,0.93,1,0.9,1,1,0.43,0.63,0.83)
 cb <- c('max','max','max','max','max')
 FuzzyTOPSISLinear(d,w,cb)

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