For the solution of large sparse nonnegative constrained least squares (NNLS) problems, a new iterative method is proposed by using conjugate gradient least squares (CGLS) method for inner iterations and the modulus-type iterative method in the outer iterations for the solution of linear complementarity problem (LCP) resulting from Karush-Kuhn-Tucker (KKT) conditions of the NNLS problem. Theoretical convergence analysis including the optimal choice of the parameter matrix is presented for the proposed method. Numerical experiments show the efficiency of the proposed method compared to projection-type methods with less iteration steps and CPU time.
Zheng et al. (Thu,) studied this question.
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