GLOBAL OPTIMIZATION BY MULTILEVEL SEARCH

被引：2

作者：

GOERTZEL, B

机构：

[1] Department of Mathematics, University of Nevada, Las Vegas, Nevada

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 1992年 / 75卷 / 02期

关键词：

MULTILEVEL METHODS; GLOBAL OPTIMIZATION; MONTE-CARLO METHODS;

D O I：

10.1007/BF00941477

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 new approach to the global optimization of functions with extremely rugged graphs is introduced. This multilevel search method is both an algorithm and a meta-algorithm, a logic for regulating optimization done by other algorithms. First, it is examined in the one-dimensional case theoretically and through simple examples. Then, to deal with higher dimensions, multilevel search is combined with the Monte Carlo method; this hybrid algorithm is tested on standard problems and is found to perform extremely well for a derivative-free method.

引用

页码：423 / 432

页数：10