摘要
遗传算法（ｇｅｎｅｔｉｃ ａｌｇｏｒｉｔｈｍ）是基于 Ｄａｒｗｉｎ的进化论和 Ｍｅｎｄａｌ遗传学说而形成的新算法，具有全局收敛性和并行性，适用性广，并要求较少的先验知识，现在已广泛应用于优化、模式识别等方面．本文简要地介绍了简单遗传算法的基本过程及其数学基础；并从编码机制、收敛性和算子的研究等方面详细地阐述了遗传算法理论的发展；对约束处理方式、适应值函数的迭取等方面的研究进行分析和评论；最后还提出遗传算法存在的主要问题和展望．
As a newly developed algorithm, the genetic algorithm, arose from the theory of evolution and genetics. It is of global convergence and parallelism. Now it has become an important part of computation intelligence. The paper briefly introduces the procedure of simple genetic algorithm and its mathematical foundation. Some developments and evaluations of encoding, convergence and operators are discussed in details. The constraint handling and the choice of fitness function are analyzed. Some suggestions for further research are given.
出处
《力学进展》
EI
CSCD
北大核心
2002年第1期26-40,共15页
Advances in Mechanics
基金
国家杰出青年科学基金(19525206)
国家重点基础研究专项经费(G1999032805)资助项目
关键词
遗传算法
适应值
约束处理
结构优化
生物进化
人工自适应系统
genetic algorithm (GA), fitness function, constraint handling, optimization The project supported by the Scientific Funds for National Outstanding Found Researchers (19525206) and the Special Funds for national Key Basic Rearch of China (G1999
