GENETIC ALGORITHMS - PRINCIPLES OF NATURAL-SELECTION APPLIED TO COMPUTATION
GENETIC ALGORITHMS - PRINCIPLES OF NATURAL-SELECTION APPLIED TO COMPUTATION
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DOI：
10.1126/science.8346439
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发表时间：
1993-08-13
期刊：
影响因子：
56.9
通讯作者：
FORREST, S
中科院分区：
文献类型：
--
作者：
FORREST, S
遗传算法是发生在计算机上的一种进化形式。遗传算法是一种搜索方法，既可以用来解决问题，也可以用来为进化系统建模。通过各种映射技术和适当的适应度测量，可以定制遗传算法来进化出许多类型的问题的解决方案，包括函数的优化或确定序列的正确顺序。数学分析已经开始解释遗传算法是如何工作的，以及如何最好地使用它们。最近，遗传算法已被用于对包括免疫系统在内的几个自然进化系统进行建模。
A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are a search method that can be used for both solving problems and modeling evolutionary systems. With various mapping techniques and an appropriate measure of fitness, a genetic algorithm can be tailored to evolve a solution for many types of problems, including optimization of a function or determination of the proper order of a sequence. Mathematical analysis has begun to explain how genetic algorithms work and how best to use them. Recently, genetic algorithms have been used to model several natural evolutionary systems, including immune systems.