A globally convergent trust region algorithm for optimization with general constraints and simple bounds |
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Authors: | Chen Zhongwen Han Jiye Han Qiaoming |
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Affiliation: | (1) Department of Mathematics, Suzhou University, 215000 Suzhou, China;(2) Institute of Applied Mathematics, the Chinese Academy of Sciences, 100080 Beijing, China |
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Abstract: | In this paper, we introduce a concept of substationary points and present a new trust region-based method for the optimization problems with general nonlinear equality constraints and simple bounds. Without the linear independent assumption on the gradients of the equalitiy constraints, we prove the global convergence results for the main algorithm and indicate that they extend the results on SQP and those on trust region methods for equality constrained optimizstion and for optimization with simple bounds. Moreover, since any nonlinear programming problem can be converted into the standard nonlinear programming by introducing slack variables, the trust region method preseated in this paper can be used for solving general nonlinear programming problems. |
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Keywords: | Trust region method global convergence nonlinear equality constraints substationary point |
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