An Efficient Algorithm for the Quadratic Programming Problem with Inequality Constraints

The solution to the general linear problem Ax=y with side conditions can be interpreted as a quadratic optimization problem. Such a requirement arises in the solution of illposed problems where the method of regularization is exploited. A compact quadratic optimization procedure is presented which obviates the requirement to invert large matrices, encountered in typical applications, and thereby reduce computation time and errors due to numerical round-off.