A finite gradient-projective solver for a quadratic programming problem

摘要

A minimization method for a quadratic functional with linear constraints is proposed. The method obtains a solution in a finite number of steps determined by the choice of the initial guess, and the number of operations at each step depends polynomially on the dimension of the problem. The method does not use any a priori information.