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Modified active set projected spectral gradient method for bound constrained optimization. (English) Zbl 1221.90081

Summary: By means of an active set strategy, we present a projected spectral gradient algorithm for solving large-scale bound constrained optimization problems. A nice property of the active set estimation technique is that it can identify the active set at the optimal point without requiring strict complementary condition, which is potentially used to solve degenerated optimization problems. Under appropriate conditions, we show that this proposed method is globally convergent. We also do some numerical experiments by using some bound constrained problems from CUTEr library. The numerical comparisons with SPG, TRON, and L-BFGS-B show that the proposed method is effective and promising.

MSC:

90C30 Nonlinear programming
90C52 Methods of reduced gradient type
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