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计算机工程 ›› 2011, Vol. 37 ›› Issue (21): 170-172,175. doi: 10.3969/j.issn.1000-3428.2011.21.058

• 人工智能及识别技术 • 上一篇    下一篇

用于数独求解的几何粒子群优化算法设计

肖华勇,马 雷,温金环   

  1. (西北工业大学理学院,西安 710129)
  • 收稿日期:2011-04-12 出版日期:2011-11-05 发布日期:2011-11-05
  • 作者简介:肖华勇(1970-),男,副教授、博士,主研方向:几何粒子群优化算法;马 雷,硕士;温金环,讲师、博士

Design of Geometric Particle Swarm Optimization Algorithm for Sudoku Solving

XIAO Hua-yong, MA Lei, WEN Jin-huan   

  1. (School of Science, Northwestern Polytechnical University, Xi’an 710129, China)
  • Received:2011-04-12 Online:2011-11-05 Published:2011-11-05

摘要: 针对只有唯一解的数独问题(即标准数独),利用改进的几何粒子群优化算法进行求解,将几何粒子群优化算法应用到数独中,解决数独求解过程中存在的局部最优解问题。通过实例讨论求解过程中最佳参数的选择,并得出较理想的结果。实验结果表明,该方法能够有效解决数独问题。

关键词: 数独, 唯一解, 几何粒子群优化, 适应度函数

Abstract: This paper proposes a new method to solve standard sudoku with unique solution, applying the improved Geometric Particle Swarm Optimization(GPSO) algorithm. It includes specific details of applying the GPSO algorithm to sudoku and improved techniques to some problems in the process of solving sudoku. It discusses the choice of the best parameter in the process of solution through the example, and gives the ideal result. Experimental results show that this method can effectively solve the sudoku problem.

Key words: sudoku, unique solution, Geometric Particle Swarm Optimization(GPSO), fitness function

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