On Tue, 7 May 2013, Jeffrey Kantor wrote:
Also note that the "Big M" technique commonly used to implement logical constraints as an MILP needs to be 'tuned' to work effectively. A proper value of M is data dependent, so the automatic translation of logical constraints to an MILP is not a trivial issue.
H[*] parameters given by problem for some j in S, X[j]<=H[j] b[*] added binary variables SUM b[j] = 1 j in S M[*] parameters to be selected for all j in S, X[j]<=H[j]+(1-b[j])*M[j] Select M[*] so that for all j, b[j]==0 -> X[j]<=H[j]+M[j] M[j]==max(X[j])-H[j] is valid, but sometimes smaller values are available. -- Michael [email protected] "On Monday, I'm gonna have to tell my kindergarten class, whom I teach not to run with scissors, that my fiance ran me through with a broadsword." -- Lily _______________________________________________ Help-glpk mailing list [email protected] https://lists.gnu.org/mailman/listinfo/help-glpk
