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
Link To Document :
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