Evolutionary computation

被引:1
|
作者
Schoenauer, M [1 ]
Michalewicz, Z
机构
[1] Ecole Polytech, URA CNRS 756, CMAP, F-91128 Palaiseau, France
[2] Univ N Carolina, Dept Comp Sci, Charlotte, NC 28223 USA
[3] Polish Acad Sci, Inst Comp Sci, PL-01237 Warsaw, Poland
来源
CONTROL AND CYBERNETICS | 1997年 / 26卷 / 03期
关键词
evolutionary computation; self-adaptation; parallelism;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Evolutionary computation techniques have received a lot of attention regarding their potential as optimization techniques for complex real-world problems. These techniques, based on the powerful principle of "survival of the fittest", model some natural phenomena of genetic inheritance and Darwinian strife for survival; they also constitute an interesting category of modern heuristic search. This introductory article presents the main paradigms of evolutionary algorithms (genetic algorithms, evolution strategies, evolutionary programming, genetic programming) as well as other (hybrid) methods of evolutionary computation. Two particular research directions (parallel evolutionary techniques and self-adaptation) are discussed further in the last part of this paper.
引用
收藏
页码:307 / 338
页数:32
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