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#library(MCDA)
# the value functions
v<-list(
Price = array(c(30, 0, 16, 0, 2, 0.0875),
dim=c(2,3), dimnames = list(c("x", "y"), NULL)),
Time = array(c(40, 0, 30, 0, 20, 0.025, 10, 0.9),
dim = c(2, 4), dimnames = list(c("x", "y"), NULL)),
Comfort = array(c(0, 0, 1, 0, 2, 0.0125, 3, 0.0125),
dim = c(2, 4), dimnames = list(c("x", "y"), NULL)))
# the performance table
performanceTable <- rbind(
c(3,10,1),
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")
# criteria to be minimized or maximized
criteriaMinMax <- c("min","min","max")
names(criteriaMinMax) <- colnames(performanceTable)
# the transformed performance table
normalizedPerformanceTable <- applyPiecewiseLinearValueFunctionsOnPerformanceTable(v,performanceTable)
correctResult <- rbind(c(0.08125,0.9,0),
c(0.075,0.025,0.0125),
c(0.0875,0.025,0),
c(0.0625,0,0),
c(0,0,0.0125))
rownames(correctResult) <- c("RER","METRO1","METRO2","BUS","TAXI")
colnames(correctResult) <- c("Price","Time","Comfort")
stopifnot(identical(normalizedPerformanceTable,correctResult))
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