Mathematical Programming Computation, Volume 1, Issue 4, December 2009
Information-based branching schemes for binary linear mixed integer problems
Fatma Kilinc Karzan, George L. Nemhauser, Martin W.P. Savelsbergh
Branching variable selection can greatly affect the effectiveness and efficiency of a branch-and-bound algorithm. Traditional approaches to branching variable selection rely on estimating the effect of the candidate variables on the objective function. We propose an approach which is empowered by exploiting the information contained in a family of fathomed subproblems, collected beforehand from an incomplete branch-and-bound tree. In particular, we use this information to define new branching rules that reduce the risk of incurring inappropriate branchings. We provide computational results that demonstrate the effectiveness of the new branching rules on various benchmark instances.
Full Text: PDF
Imprint and privacy statement
For the imprint and privacy statement we refer to the Imprint of ZIB.
© 2008-2022 by Zuse Institute Berlin (ZIB).