PROMETHEEI: PROMETHEE I

In MCDA: Support for the Multicriteria Decision Aiding Process

PROMETHEE I

Description

The PROMETHEE I constructs preference indices from the criteria evaluations of alternatives and outputs three preference relations (P - preference, I - indifference, R - incomparability) based on the outranking flows between the alternatives.

Usage

PROMETHEEI(
  performanceTable,
  preferenceFunction,
  preferenceThreshold,
  indifferenceThreshold,
  gaussParameter,
  criteriaWeights,
  criteriaMinMax
)

Arguments

performanceTable	Matrix containing the evaluation table. Each row corresponds to an alternative, and each column to a criterion. Rows (resp. columns) must be named according to the IDs of the alternatives (resp. criteria).
preferenceFunction	A vector with preference functions.preferenceFunction should be equal to Usual,U-shape,V-shape,Level,V-shape-Indiff or Gaussian. The elements are named according to the IDs of the criteria.
preferenceThreshold	A vector containing threshold of strict preference. The elements are named according to the IDs of the criteria.
indifferenceThreshold	A vector containing threshold of indifference. The elements are named according to the IDs of the criteria.
gaussParameter	A vector containing parameter of the Gaussian preference function. The elements are named according to the IDs of the criteria.
criteriaWeights	Vector containing the weights of the criteria. The elements are named according to the IDs of the criteria.
criteriaMinMax	Vector containing the preference direction on each of the criteria. "min" (resp. "max") indicates that the criterion has to be minimized (maximized). The elements are named according to the IDs of the criteria.

Value

The function returns three matrices: The first one contains the preference relations between the alternatives, the second one contains the indifference relations between the alternatives and the third one contains the incomparability relations between the alternatives.

Examples

# The evaluation table

performanceTable <- rbind(
  c(1,10,1),
  c(4,20,2),
  c(2,20,0),
  c(6,40,0),
  c(30,30,3))
rownames(performanceTable) <- c("RER","METRO1","METRO2","BUS","TAXI")
colnames(performanceTable) <- c("Price","Time","Comfort")

# The preference functions 
preferenceFunction<-c("Gaussian","Level","V-shape-Indiff")

#Preference threshold
preferenceThreshold<-c(5,15,3)
names(preferenceThreshold)<-colnames(performanceTable)

#Indifference threshold
indifferenceThreshold<-c(3,11,1)
names(indifferenceThreshold)<-colnames(performanceTable)

#Parameter of the Gaussian preference function
gaussParameter<-c(4,0,0)
names(gaussParameter)<-colnames(performanceTable)

#weights

criteriaWeights<-c(0.2,0.3,0.5)
names(criteriaWeights)<-colnames(performanceTable)

# criteria to minimize or maximize

criteriaMinMax<-c("min","min","max")
names(criteriaMinMax)<-colnames(performanceTable)

PROMETHEEI(performanceTable, preferenceFunction,preferenceThreshold,
          indifferenceThreshold,gaussParameter,criteriaWeights,criteriaMinMax)

MCDA documentation built on Nov. 24, 2023, 5:10 p.m.