IMPLEMENTATION OF BRANCH AND BOUND METHOD FOR CONVEX OPTIMIZATION PROBLEM - Hariadi, Victor; Soelaiman, Rully (Proceedings of KNASTIK, 2012)
Convex optimization is one of important areas in nonlinear programming, both fromthe mathematical and application viewpoints. Numerous real world problems arenaturally expressed as quadratic programming problems. In non linear programming,it is necessary to use a method to get global optimal value in order to not get trapped inlocal optimal value. Branch and bound method in non linear programming known asone of global optimization technique.In this research we implement branch and boundmethod with relaxation process in the problem to get global optimization from convexprogramming. The boundary of sub problem will be considering using reformulationfrom quadratic with KKT condition. Experiment was accomplished on quadra1ticprogramming problems. The results showed that using reformulation from quadraticwith Karush-Kuhn-Tucker (KKT) condition for bounding the problems helps to getoptimal solution in branch and bound method.