ADVANCES OF GENETIC ALGORITHMS IN STRUCTURAL OPTIMIZATION
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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、适应值函数的选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.Abstract: As a newly developed algorithm, the genetic algorithm, arose from the theory of evolution and genetics. It is of globalconvergence and parallelism. Now it has become an important partof 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.
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Key words:
- genetic algorithm (GA) /
- fitness function /
- constrainthandling /
- optimization
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