tests/MRSortInferenceApprox.R

In paterijk/MCDA: Support for the Multicriteria Decision Aiding Process

# ranking some students (from the article on Integrating Large Performance Differences in MR Sort by Meyer and Olteanu, 2015)

library(MCDA)

# the performance table

performanceTable <- rbind(c(10,10,9),c(10,9,10),c(9,10,10),c(9,9,10),c(9,10,9),c(10,9,9),
                          c(10,10,7),c(10,7,10),c(7,10,10),c(9,9,17),c(9,17,9),c(17,9,9),
                          c(7,10,17),c(10,17,7),c(17,7,10),c(7,17,10),c(17,10,7),c(10,7,17),
                          c(7,9,17),c(9,17,7),c(17,7,9),c(7,17,9),c(17,9,7),c(9,7,17))

rownames(performanceTable) <- c("a1","a2","a3","a4","a5","a6","a7","a8","a9","a10","a11","a12","a13","a14","a15","a16","a17","a18","a19","a20","a21","a22","a23","a24")

colnames(performanceTable) <- c("c1","c2","c3")

assignments <-c("P","P","P","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F")

names(assignments) <- rownames(performanceTable)

categoriesRanks <-c(1,2)

names(categoriesRanks) <- c("P","F")

criteriaMinMax <- c("max","max","max")

names(criteriaMinMax) <- colnames(performanceTable)

set.seed(1)

x<-MRSortInferenceApprox(performanceTable, assignments, categoriesRanks, 
                         criteriaMinMax, veto = TRUE,
                         alternativesIDs = c("a1","a2","a3","a4","a5","a6","a7"))

print(x)

ElectreAssignments<-MRSort(performanceTable, x$profilesPerformances, categoriesRanks,
                        x$criteriaWeights, criteriaMinMax, x$majorityThreshold, criteriaVetos=x$vetoPerformances, alternativesIDs = c("a1","a2","a3","a4","a5","a6","a7"))

print(all(ElectreAssignments == assignments[c("a1","a2","a3","a4","a5","a6","a7")]))

stopifnot(all(assignments[c("a1","a2","a3","a4","a5","a6","a7")] == ElectreAssignments))