DocumentCode
710046
Title
Improved ant colony genetic algorithm hybrid for Sudoku solving
Author
Mantere, Timo
Author_Institution
Dept. of Comput. Sci., Univ. of Vaasa, Vaasa, Finland
fYear
2013
fDate
15-18 Dec. 2013
Firstpage
274
Lastpage
279
Abstract
In this paper we introduce our new improved version of ant colony optimization/genetic algorithm hybrid for Sudoku puzzle solving. Sudoku is combinatorial number puzzle that had become worldwide phenomenon in the last decade. It has also become popular mathematical test problem in order to test new optimization ideas and algorithms for combinatorial problems. In this paper we present our new ideas for populations sorting and elitism rules in order to improve our earlier evolutionary algorithm based Sudoku solvers. Experimental results show that the new ideas significantly improved the speed of Sudoku solving.
Keywords
ant colony optimisation; combinatorial mathematics; games of skill; genetic algorithms; Sudoku solvers; ant colony genetic algorithm hybrid; ant colony optimization; combinatorial number puzzle; elitism rules; evolutionary algorithm; mathematical test problem; populations sorting; Benchmark testing; Cultural differences; Genetic algorithms; Genetics; Heuristic algorithms; Ant colony optimization; Sudoku; combinatorial problems; cultural algorithms; genetic algorithms; puzzle solving;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Technologies (WICT), 2013 Third World Congress on
Conference_Location
Hanoi
Type
conf
DOI
10.1109/WICT.2013.7113148
Filename
7113148
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