ON A CLASS OF HYBRID METHODS FOR SMOOTH CONSTRAINED OPTIMIZATION

被引：15

作者：

KLEINMICHEL, H ^{[1
]}

RICHTER, C ^{[1
]}

SCHONEFELD, K ^{[1
]}

机构：

[1] KOTHEN UNIV TECHNOL,DEPT MATH & COMP SCI,KOTHEN,GERMANY

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 1992年 / 73卷 / 03期

关键词：

NONLINEAR PROGRAMMING ALGORITHMS; LOCALLY SUPERLINEARLY CONVERGENT METHODS; GLOBALLY CONVERGENT METHODS; HYBRID TECHNIQUES;

D O I：

10.1007/BF00940052

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

With reference to smooth nonlinearly constrained optimization problems, we consider combinations of locally superlinearly convergent methods with globally convergent ones. The aim of this paper is threefold: to give a survey on well-known as well as possibly unknown hybrid optimization methods, based on a special construction principle; to present a general convergence result for the class of hybrid algorithms; and to derive further methods for this class with new convergence properties.

引用

页码：465 / 499

页数：35

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