遗传算法(Genetic Algorithm,GA)是一种抽象于生物进化过程的基于自然选择和生物遗传机制的优化技术.

遗传算法的基本原理

在遗传算法的执行过程中,每一代有许多不同的种群个体(染色体 )同时存在。这些染色体中哪个保留(生存)、哪个淘汰(死亡),是根据 它们对环境的适应能力来决定的,适应性强的有更多的机会保留下来 。适应性强弱是通过计算适应性函数f(x)的值来判别的,这个值称为适应值。适应值函数f(x)的构成与目标函数有密切关系,往往是目标函数的变种。-Genetic Algorithm (Genetic Algorithm, GA) is an abstract in the process of biological evolution based on natural selection and genetic mechanisms of biological optimization technology. The basic principles of genetic algorithm genetic algorithm in the implementation process, each generation has a number of different populations of individuals ( chromosome) at the same time. Which of these chromosomes reservation (survival), which eliminated (death), is based on their ability to adapt to the environment to decide adaptable have more opportunities to retain it. Adaptation strength is by calculating the adaptive function f (x) to determine the value, this value is called fitness. Fitness function f (x) the composition and the objective function is closely related to the objective function is often a variant.