Forrest S
Department of Computer Science, University of New Mexico, Albuquerque 87131-1386.
Science. 1993 Aug 13;261(5123):872-8. doi: 10.1126/science.8346439.
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 of 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.
遗传算法是一种在计算机上发生的进化形式。遗传算法是一种搜索方法,可用于解决问题和对进化系统进行建模。通过各种映射技术和适当的适应度度量,可以定制遗传算法以针对许多类型的问题进化出解决方案,包括优化函数或确定序列的正确顺序。数学分析已开始解释遗传算法的工作原理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种自然进化系统进行建模。