Complete decomposition algorithm for nonconvex separable optimization problems and applications

Abstract

In this paper, we present a complete decomposition algorithm for nonconvex separable optimization problems applied in the optimal control problems. This complete decomposition algorithm combines recursive quadratic programming with the dual method. When our algorithm is applied to discretized optimal control problems, a simple and parallel computation and a simple and regular data flow pattern between consecutive computational steps results. This paper also suggests an approach for developing a hardware implementation of our algorithm and gives an estimation of the execution time needed to solve a practical example.