Interior point gradient algorithm for totally nonnegative least-squares problems in inequality sense

摘要

In this paper we study a scaled interior-point gradient algorithm for totally nonnegative least-squares problems in the inequality sense. The global convergence of the algorithm is established. Finally, extensive computational comparison with the so-called generalized Newton algorithm is given showing the superior performance of the gradient-based algorithm.