library(kappalab) ## some alternatives a <- c(18,11,18,11,11) b <- c(18,18,11,11,11) c <- c(11,11,18,18,11) d <- c(18,11,11,11,18) e <- c(11,11,18,11,18) ## preference threshold relative ## to the preorder of the alternatives delta.C <- 1 ## corresponing Choquet preorder constraint matrix Acp <- rbind(c(d,a,delta.C), c(a,e,delta.C), c(e,b,delta.C), c(b,c,delta.C) ) ## a Shapley preorder constraint matrix ## Sh(1) - Sh(2) >= -delta.S ## Sh(2) - Sh(1) >= -delta.S ## Sh(3) - Sh(4) >= -delta.S ## Sh(4) - Sh(3) >= -delta.S ## i.e. criteria 1,2 and criteria 3,4 ## should have the same global importances delta.S <- 0.01 Asp <- rbind(c(1,2,-delta.S), c(2,1,-delta.S), c(3,4,-delta.S), c(4,3,-delta.S) ) ## a Shapley interval constraint matrix ## 0.3 <= Sh(1) <= 0.9 Asi <- rbind(c(1,0.3,0.9)) ## an interaction preorder constraint matrix ## such that I(12) = I(34) delta.I <- 0.01 Aip <- rbind(c(1,2,3,4,-delta.I), c(3,4,1,2,-delta.I)) ## an interaction interval constraint matrix ## i.e. -0.20 <= I(12) <= -0.15 delta.I <- 0.01 Aii <- rbind(c(1,2,-0.2,-0.15)) ## a minimum variance 2-additive solution min.var <- mini.var.capa.ident(5,2,A.Choquet.preorder = Acp) m <- min.var$solution m ## the resulting global evaluations rbind(c(a,mean(a),Choquet.integral(m,a)), c(b,mean(b),Choquet.integral(m,b)), c(c,mean(c),Choquet.integral(m,c)), c(d,mean(d),Choquet.integral(m,d)), c(e,mean(e),Choquet.integral(m,e))) ## the Shapley value Shapley.value(m) ## a minimum variance 3-additive more constrainted solution min.var2 <- mini.var.capa.ident(5,3, A.Choquet.preorder = Acp, A.Shapley.preorder = Asp) m <- min.var2$solution m rbind(c(a,mean(a),Choquet.integral(m,a)), c(b,mean(b),Choquet.integral(m,b)), c(c,mean(c),Choquet.integral(m,c)), c(d,mean(d),Choquet.integral(m,d)), c(e,mean(e),Choquet.integral(m,e))) Shapley.value(m) ## a minimum variance 5-additive more constrainted solution min.var3 <- mini.var.capa.ident(5,5, A.Choquet.preorder = Acp, A.Shapley.preorder = Asp, A.Shapley.interval = Asi, A.interaction.preorder = Aip, A.interaction.interval = Aii) m <- min.var3$solution m rbind(c(a,mean(a),Choquet.integral(m,a)), c(b,mean(b),Choquet.integral(m,b)), c(c,mean(c),Choquet.integral(m,c)), c(d,mean(d),Choquet.integral(m,d)), c(e,mean(e),Choquet.integral(m,e))) summary(m)