A parallel processing algorithm for a class of quadratic programming problems and applications

In this paper, we present a parallel dual-type algorithm for solving a class of quadratic programming problems. Our algorithm is suitable for implementation in a distributed computer network and can be used as a basic optimization tool for handling optimization problems of large distributed system. Thus, combining our algorithm with quadratic programming method, we can solve constrained nonlinear programming problems such as power system state estimation problems with power flow balance constraints on no load and no generation buses. We have tested our algorithm on several state estimation examples and experienced a dramatic speed up ratio in comparing the sequential version of our method with IMSL subroutine.