Department of Applied Mathematics & Physics, Kyoto University

Technical Report 2001-009 (October 15, 2001)

Global Optimization Algorithms for General Quadratic Programming
by R. Enkhbat and T. Ibaraki

PostScript File

In this paper we consider the general quadratic programming, which is classified into: convex quadratic maximization, convex quadratic minimization and indefinite quadratic programming. Based on the optimality conditions (local and global) we propose algorithms for solving those problems. The proposed algorithms use linear programming as subproblems and generate a sequence of local maximizers or stationary points. It is shown that the algorithms are finite and convergent under appropriate conditions. As applications, some real-world problems arisen in the response surface, one of the main topics in the design of experiment, have been solved numerically by the algorithms.