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Projected quasi-Newton algorithm with trust region for constrained optimization

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Abstract

In Ref. 1, Nocedal and Overton proposed a two-sided projected Hessian updating technique for equality constrained optimization problems. Although local two-step Q-superlinear rate was proved, its global convergence is not assured. In this paper, we suggest a trust-region-type, two-sided, projected quasi-Newton method, which preserves the local two-step superlinear convergence of the original algorithm and also ensures global convergence. The subproblem that we propose is as simple as the one often used when solving unconstrained optimization problems by trust-region strategies and therefore is easy to implement.

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Communicated by D. F. Shanno

This research was supported in part by the National Natural Science Foundation of China.

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Zhang, J.Z., Zhu, D.T. Projected quasi-Newton algorithm with trust region for constrained optimization. J Optim Theory Appl 67, 369–393 (1990). https://doi.org/10.1007/BF00940481

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