Solving and analyzing Sudokus with cultural algorithms

This paper studies how cultural algorithm suits to solving and analyzing Sudoku puzzles. Sudoku is a number puzzle that has recently become a worldwide phenomenon. It can be regarded as a combinatorial problem, but when solved with evolutionary algorithms it can also be handled as a constraint satisfaction or multi-objective optimization problem. The objectives of this study were 1) to test if a cultural algorithm with a belief space solves Sudoku puzzles more efficiently than a normal permutation genetic algorithm, 2) to see if the belief space gathers information that helps analyze the results and improve the method accordingly, 3) to improve our previous Sudoku solver presented in CEC2007. Experiments showed that proposed the cultural algorithm performed slightly better than the previous genetic algorithm based Sudoku solver.