Hans W Borchers <hwborchers <at> googlemail.com> writes:
> # Prepare inputs for MILP solver
> obj <- c(rep(0, n), 0, 1, 1, 0)
> typ <- c(rep("B", n), "B", "C", "C", "B")
> mat <- matrix(c( s, -z, -1, 1, 0, # a = a_p + a_m
> rep(0, n), 1, 0, 0, 0, # constant term
> rep(0, n), 0, 1, 0, -M, # a_p <= M * d0
> rep(0, n), 0, 0, 1, M, # a_m <= M * (d0-1)
> rep(1, n), 0, 0, 0, 0), # subset size <= k
> nrow=5, byrow=T)
> dir <- c("==", "==", "<=", "<=", "<=")
> rhs <- c(0, 1, 0, M, k)
> max <- FALSE
You can drop the binary variable d0.
The condition "one of a_p,a_m is zero" holds
automatically as we are minimizing a_p+a_m.
----------------------------------------------------------------
Erwin Kalvelagen
Amsterdam Optimization Modeling Group
er...@amsterdamoptimization.com
http://amsterdamoptimization.com
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