# 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)
#Preference indices
preferenceTable<-PROMETHEEPreferenceIndices(performanceTable, preferenceFunction,
preferenceThreshold, indifferenceThreshold,
gaussParameter, criteriaWeights,
criteriaMinMax)
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