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
收藏
页码：465 / 499
页数：35
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