摘要
遗传算法是一种基于生物进化机制和原理并引用随机理论的优化搜索方法－ 它具有全局收敛特点，可以被用来解决各种复杂的实际问题－ 如工程优化设计、人工智能和决策系统等－ 本文在讨论遗传算法的基本原理框架的基础上，提出相应的编码方法和计算适应值方法－ 为了平衡ＧＡｓ的深度和广度搜索矛盾，修改遗传算子。
Genetic algorithms are an optimization search based on simulating natural genetics and Darwinian evolution and the theory of random search Because of the fact that Gas have global convergence, it can be used to solve many complicated problems For example, engineering optimization design, AI and decision system and so on In this paper, an encoding method and a formula of computing fitness are given, based on discussing the basic principle frame of Gas In order to balance the contradiction between depth search and breadth search of Gas, the genetic operations are modified Finally, a typical example and commentary are given
出处
《福州大学学报（自然科学版）》
CAS
CSCD
1999年第5期14-18,共5页
Journal of Fuzhou University(Natural Science Edition)
关键词
遗传算法
全局优化
随机搜索
适应性
解
genetic algorithms
global optimization
random search
fitness
