GENETIC ALGORITHMS - A SURVEY
GENETIC ALGORITHMS - A SURVEY
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DOI：
10.1109/2.294849
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发表时间：
1994-06-01
期刊：
影响因子：
2.2
通讯作者：
PATNAIK, LM
中科院分区：
文献类型：
--
作者：
SRINIVAS, M;PATNAIK, LM
遗传算法提供了一种替代传统优化技术的方法，它使用定向随机搜索在复杂的地形中寻找最优解。我们介绍了遗传算法的艺术和科学，并综述了当前遗传算法理论和实践中存在的问题。我们没有提供详细的研究，相反，我们提供了一个迷宫般的GA研究的快速指南。首先，我们将遗传算法与自然界中的搜索过程进行了类比。然后我们描述了Holland在1975年引入的遗传算法和遗传算法的工作原理。在概述了改进Holland遗传算法的技术和一些截然不同的方法之后，我们综述了与建模、动力学和欺骗相关的遗传算法理论的进展。
Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex landscapes. We introduce the art and science of genetic algorithms and survey current issues in GA theory and practice. We do not present a detailed study, instead, we offer a quick guide into the labyrinth of GA research. First, we draw the analogy between genetic algorithms and the search processes in nature. Then we describe the genetic algorithm that Holland introduced in 1975 and the workings of GAs. After a survey of techniques proposed as improvements to Holland's GA and of some radically different approaches, we survey the advances in GA theory related to modeling, dynamics, and deception.<>