Development and analysis of genetic algorithms: Sudoku case study
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Copyright © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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This paper discusses the design and subsequent analysis of software implementing a configurable genetic algorithm. The genetic algorithm is primarily targeted towards the solving of Sudoku puzzles. Sudoku is regarded as an ideal test-bed for algorithm development due to the fact that it is a constrained optimisation problem that belongs to the NP-complete class of computational problems. The aim of this paper is to outline the various features currently implemented in the software, and to present preliminary results of an analysis of various aspects of the underlying genetic algorithm.
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