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Volume 4, Issue 3, 1 December 2020, Pages 469-482
Abstract. In this paper, with the aid of square quadratic proximal (SQP) method and the self-adaptive adjustment rule, we propose an SQP alternating direction method for solving the linearly constrained separable convex programming with three separable operators. Under standard assumptions, the global convergence of the proposed method is proved. Its efficiency is also verified via some numerical experiments.
How to Cite this Article:
Abdellah Bnouhachem, A descent SQP alternating direction method for minimizing the sum of three convex functions, J. Nonlinear Var. Anal. 4 (2020), 469-482.