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GLOBAL CONVERGENCE OF NONMONOTONIC TRUST REGION ALGORITHM FOR NONLINEAR OPTIMIZATION 被引量:1

GLOBAL CONVERGENCE OF NONMONOTONIC TRUST REGION ALGORITHM FOR NONLINEAR OPTIMIZATION
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摘要 A trust region algorithm for equality constrained optimization is given in this paper.The algorithm does not enforce strict monotonicity of the merit function for every iteration.Global convergence of the algorithm is proved under the same conditions of usual trust region method. A trust region algorithm for equality constrained optimization is given in this paper.The algorithm does not enforce strict monotonicity of the merit function for every iteration.Global convergence of the algorithm is proved under the same conditions of usual trust region method.
出处 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2000年第2期201-210,共10页 高校应用数学学报(英文版)(B辑)
基金 Supported by NSFC!(19771034)
关键词 Nonmonotone algorithm equality constrains trust region method global convergence. Nonmonotone algorithm,equality constrains,trust region method,global convergence.
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