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

页码：185 / 206

页数：22