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A TRUST REGION METHOD WITH A CONIC MODEL FOR NONLINEARLY CONSTRAINED OPTIMIZATION
作者姓名:Wang  Chengjing
作者单位:Dept.of Math., Zhejiang Univ., Hangzhou 310028, China.
摘    要:Trust region methods are powerful and effective optimization methods.The conic model method is a new type of method with more information available at each iteration than standard quadratic-based methods.The advantages of the above two methods can be combined to form a more powerful method for constrained optimization.The trust region subproblem of our method is to minimize a conic function subject to the linearized constraints and trust region bound.At the same time,the new algorithm still possesses robust global properties.The global convergence of the new algorithm under standard conditions is established.

关 键 词:信任区域法  二次曲线模型  拘泥最优化  非线性规划
收稿时间:2006-02-23

A trust region method with a conic model for nonlinearly constrained optimization
Wang Chengjing.A TRUST REGION METHOD WITH A CONIC MODEL FOR NONLINEARLY CONSTRAINED OPTIMIZATION[J].Applied Mathematics A Journal of Chinese Universities,2006,21(3):263-275.
Authors:Wang Chengjing
Institution:(1) Dept. of Math., Zhejiang Univ., 310028 Hangzhou, China
Abstract:Trust region methods are powerful and effective optimization methods. The conic model method is a new type of method with more information available at each iteration than standard quadratic-based methods. The advantages of the above two methods can be combined to form a more powerful method for constrained optimization. The trust region subproblem of our method is to minimize a conic function subject to the linearized constraints and trust region bound. At the same time, the new algorithm still possesses robust global properties. The global convergence of the new algorithm under standard conditions is established.
Keywords:trust region method  conic model  constrained optimization  nonlinear programming  
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