Recent advances in solving some optimization problems in graphs by quadratic programming
Résumé
We review Quadratic Convex Reformulation (QCR) for quadratic pro-
grams with general integer variables. This solution 2-phase approach
consist in first reformulating the quadratic program into an equivalent
other problem having a convex ob jective function. The second phase
relies on MIP solvers that solve the reformulated problem by standard
branch-and-b ound. Then, we consider some graph partitioning problems
that can be formulated as quadratic programs with binary variables. We
show many enhancements of the standard QCR method that efficiently
solve graph partitioning problems