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A family of supermemory gradient projection methods for constrained optimization. (English) Zbl 1145.90465
Summary: A family of supermemory gradient projection methods for solving the convex constrained optimization problem is presented in this article. It is proven to have stronger convergence properties than the traditional gradient projection method. In particular, it is shown to be globally convergent if the objective function is convex.

MSC:
90C52 Methods of reduced gradient type
90C25 Convex programming
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