AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION

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	AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION
其他题名	An adaptive trust region method for equality constrained optimization
	Zhang Juliang 1; Zhang Xiangsun 2; Zhuo Xinjian 3
	2003
发表期刊	系统科学与复杂性：英文版
ISSN	1009-6124
卷号	16.0 期号:004 页码:494-505
摘要	In this paper, a trust region method for equality constrained optlmization based on nondiferentiable exact penalty is proposed. In this algorithin, the trail step is characterized by computation of its normal component being separated from computation of its tangential component, i.e., only the tangential component of the trail step is constrained by trust radius while the normal component and trail step itself have no constraints. The other main characteristic of the algorithm is the decision of trust region radius. Here, the decision of trust region radius uses the information of the gradient of objective function and reduced Hessian. However, Maratos effect will occur when we use the nondifferentiable exact penalty function as the merit function. In order to obtain the superlinear convergence of the algorithm, we use the twice order correction technique. Because of the speciality of the adaptive trust region method, we use twice order correction when p= 0 (the definition is as in Section 2) and this is different from the traditional trust region methods for equality constrained opthnization. So the computation of the algorithm in this paper is reduced. What is more, we can prove that the algorithm is globally and superlinearly convergent.
其他摘要	In this paper, a trust region method for equality constrained optimization . based on nondifferentiable exact penalty is proposed. In this algorithm, the trail step is characterized by computation of its normal component being separated from compu-tation of its tangential component, i.e., only the tangential component of the trail step is constrained by trust radius while the normal component and trail step itself have no constraints. The other main characteristic of the algorithm is the decision of trust region radius. Here, the decision of trust region radius uses the information of the gradient of objective function and reduced Hessian. However, Maratos effect will occur when we use the nondifferentiable exact penalty function as the merit function. In order to obtain the superlinear convergence of the algorithm, we use the twice order correction technique. Be-cause of the speciality of the adaptive trust region method, we use twice order correction when p = 0 (the definition is as in Section 2) and this is different from the traditional trust region methods for equality constrained optimization. So the computation of the algorithm in this paper is reduced. What is more, we can prove that the algorithm is globally and superlinearly convergent.
关键词	等式约束最优化适应性信赖域方法整体收敛超线性收敛罚函数
收录类别	CSCD
语种	中文
CSCD记录号	CSCD:1271072
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/57293
专题	中国科学院数学与系统科学研究院
作者单位	1.河北经贸大学经济管理学院 2.中国科学院数学与系统科学研究院 3.北京邮电大学
推荐引用方式 GB/T 7714	Zhang Juliang,Zhang Xiangsun,Zhuo Xinjian. AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION[J]. 系统科学与复杂性：英文版,2003,16.0(004):494-505.
APA	Zhang Juliang,Zhang Xiangsun,&Zhuo Xinjian.(2003).AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION.系统科学与复杂性：英文版,16.0(004),494-505.
MLA	Zhang Juliang,et al."AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION".系统科学与复杂性：英文版 16.0.004(2003):494-505.