Projected quasi-Newton algorithm with trust region for constrained optimization |
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Authors: | J Z Zhang D T Zhu |
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Institution: | (1) Department of Mathematics, Shanghai Normal University, Shanghai, China;(2) Present address: Department of Applied Mathematics, City Polytechnic of Hong Kong, Hong Kong |
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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.This research was supported in part by the National Natural Science Foundation of China. |
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Keywords: | Two-sided projected Hessians trust regions differentiable penalty functions global convergence two-step Q-superlinear rate constrained optimization |
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