Genetic algorithm, genetic

Genetic algorithm, genetic

I. Introduction

Genetic algorithms (GA, Genetic Algorithm) are also called evolutionary algorithms. Genetic algorithms are a heuristic search algorithm inspired by Darwin's evolution and based on the biological evolution process. Therefore, it is necessary to briefly introduce biological evolution knowledge before introducing genetic algorithms.

 

Ii. Principles

Population (Population): biological evolution is carried out in the form of a group. Such a group is called a Population. Individual: A single creature that forms a population. Gene: A genetic factor. Chromosome: contains a group of genes. Survival competition and survival of the fittest: there are many opportunities for individuals with high environmental adaptability and participation in breeding, and more future generations will be born. Individuals with low fitness have fewer opportunities to participate in reproduction and fewer offspring. Genetics and Mutation: new individuals will inherit the genes of each part of both parents, and there is a certain probability of genetic variation.

During the breeding process, Crossover occurs, Mutation occurs, and individuals with low Fitness will be gradually eliminated, while more and more individuals with high Fitness. Then, after the natural selection of N generations, the stored individual is highly adaptive.

 

Iii. Instances

Http://www.cnblogs.com/heaad/archive/2010/12/23/1914725.html

 

Reference: http://www.cnblogs.com/heaad/archive/2010/12/23/1914725.html http://baike.baidu.com/link? Url = required _