Skip to content

The aim of this project is to implement Genetic Algorithms (GAs), applied to a Sudoku problem in order to obtain the best solution. To do so, we have designed a fitness function and other appropriate genetic operators to reach an optimal solution (e.g. crossover, mutation and selection).

Notifications You must be signed in to change notification settings

m20210989/CIFO-Sudoku-GA-Group-D

Repository files navigation

CIFO-Sudoku-GA-Group-D

The aim of this project is to implement Genetic Algorithms (GAs), applied to a Sudoku problem in order to obtain the best solution. To do so, we have designed a fitness function and other appropriate genetic operators to reach an optimal solution (e.g. crossover, mutation and selection).

To run the code, run sudoku.py

About

The aim of this project is to implement Genetic Algorithms (GAs), applied to a Sudoku problem in order to obtain the best solution. To do so, we have designed a fitness function and other appropriate genetic operators to reach an optimal solution (e.g. crossover, mutation and selection).

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages