Genetic Algorithm

Genetic algorithms are computational models of the biological evolutionary processes that mimic the natural selection and genetics of Darwin's biological evolution and a method of searching for the optimal solution by simulating the natural evolutionary process.

The most important feature of this genetic algorithms implemented in this package is the scalabilit,that is to say,it's easy to extend. You could directly modifying the genetic algorithm script that has been implemented in the demo scene to get the fittest solution for solving your problem,or to extend and write your own logic to meet your needs by inheriting the "Abstract GACore" Class.

In this packag,there are three demo scene for showing the genetic algorithm process，they are the Binary Demo,the Word Demo,and the TSP Demo.

- Binary Demo:In this scene,genomes are encoded in binary form.This scene shows using genetic algorithms to find the maximum value for a given length of the binary number

- Word Demo:In this scene,genomes are encoded in char form.This scene shows using genetic algorithms to make the contents of this string converge to the contents of a string of the same length, until exactly the same.

- TSP Demo:This scene shows the travelling salesman problem(TSP).In this scene,genomes are encoded in decimal form and there are some point represent different cities，the traveling salesman must determine the shortest route that will enable him to visit each city precisely once and then return back to his starting point.

Please read the Introduction in this package for more details

If you technical questions ,please email 18311310080@163.com