Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (11): 152-155.

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Improvement of adaptive genetic algorithms and application in line simplification

REN Haiyan, CHEN Feixiang   

  1. School of Information Science & Technology, Beijing Forestry University, Beijing 100083, China
  • Online:2012-04-11 Published:2012-04-16



  1. 北京林业大学 信息学院,北京 100083

Abstract: Fixed genetic probabilities easily cause the premature and slow convergence problem. Improvement of current adaptive genetic algorithm is proposed to avoid that. Through the experiments of optimization for common test functions, this improved algorithm shows its better global optimal ability and faster convergence ability. Based on this, this improved algorithm is applied in line simplification. Simulation results show that it can maintain the overall shape, and can get better simplification results.

Key words: adaptive genetic algorithm, improvement, line simplification

摘要: 针对固定遗传概率容易引起早熟及收敛慢的问题,对现有自适应遗传算法进行了改进。通过常见测试函数优化求解试验,验证了改进算法具有更好的全局收敛性和更快的收敛速度。在此基础上,将改进算法应用于曲线化简。仿真试验表明,其不仅能够较好地保持曲线的整体形态,还能够得到形变误差更小的化简结果。

关键词: 自适应遗传算法, 改进, 曲线化简