Parallel characteristical algorithms for solving problems of global optimization

被引：39
|
作者：
Grishagin, VA
Sergeyev, YD
Strongin, RG
机构：
[1] UNIV NIZHNI NOVGOROD,SOFTWARE DEPT,NIZHNII NOVGOROD 603600,RUSSIA
[2] UNIV CALABRIA,DEIS,CNR,ISI,I-87036 RENDE,CS,ITALY
来源：
JOURNAL OF GLOBAL OPTIMIZATION | 1997年 / 10卷 / 02期
关键词：
global optimization; parallel computations; characteristical algorithms;
D O I：
10.1023/A:1008242328176
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：
A class of parallel characteristical algorithms for global optimization of one-dimensional multiextremal functions is introduced. General convergence and efficiency conditions for the algorithms of the class introduced are established. A generalization for the multidimensional case is considered. Examples of parallel characteristical algorithms and numerical experiments are presented.
引用
收藏
页码：185 / 206
页数：22
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