计算机应用 ›› 2012, Vol. 32 ›› Issue (01): 234-237.DOI: 10.3724/SP.J.1087.2012.00234

• 人工智能 • 上一篇    下一篇

改进的混合蛙跳算法

葛宇1,王学平2,梁静3   

  1. 1. 四川师范大学 基础教学学院,成都 610068
    2. 四川师范大学 数学与软件科学学院,成都 610068
    3. 成都电子机械高等专科学校 网络中心,成都 610031
  • 收稿日期:2011-06-16 修回日期:2011-08-16 发布日期:2012-02-06 出版日期:2012-01-01
  • 通讯作者: 葛宇
  • 作者简介:葛宇(1981-),男,四川西昌人,讲师,硕士,CCF会员,主要研究方向:计算智能;王学平(1965-),男,四川遂宁人,教授,博士生导师,博士,主要研究方向:不确定性的数学理论及算法;梁静(1979-),女,四川泸州人,讲师,硕士,CCF会员,主要研究方向:图形图像。
  • 基金资助:

    四川师范大学青年基金资助项目(10QNL04)

Improved shuffled frog leaping algorithm

GE Yu1,WANG Xue-ping2,LIANG Jing3   

  1. 1. College of Fundamental Education, Sichuan Normal University, Chengdu Sichuan 610068, China
    2. College of Mathematics and Soft Science, Sichuan Normal University, Chengdu Sichuan 610068, China
    3. Network Center, Chengdu Electromechanical College, Chengdu Sichuan, 610031, China
  • Received:2011-06-16 Revised:2011-08-16 Online:2012-02-06 Published:2012-01-01
  • Contact: GE Yu

摘要: 为提高混合蛙跳算法在优化问题求解中的性能,提出了一种改进混合蛙跳算法。改进算法在原算法基础上加入了变异算子,并根据算法进化过程的不同阶段和进化过程中候选解分布情况,利用模糊控制器对变异算子的变异尺度进行调整,实现了变异算子在解空间中搜索范围的动态调整。通过对优化问题中4个典型测试函数的仿真实验表明,与基本蛙跳算法和已有改进算法相比,改进算法在寻优精度、收敛速度和求解成功率上均有一倍以上的提高,尤其在高维复杂优化问题求解中体现出较强的寻优能力。

关键词: 模糊控制器, 混合蛙跳算法, 变异算子, 变异尺度

Abstract: To enhance the performance of Shuffled Frog Leaping Algorithm (SFLA) in solving optimization problems,this paper proposed an improved shuffled frog leaping algorithm. By adding mutation operator to the original algorithm, the improved algorithm regulated the scale of mutation operator via fuzzy controller, made a dynamic adjustment of mutation operator in the searching range of solution space with different phase and candidate solution distribution of evolution process. The simulation results of four typical functions of optimization problems show that the proposed algorithm can attain above twice improvement on accuracy, convergent speed and success rate, and it demonstrates a better optimization capability especially in solving the high dimensional complex optimization problem, in comparison with the basic shuffled frog leaping algorithm and the known improved algorithm.

Key words: fuzzy controller, Shuffled Frog Leaping Algorithm (SFLA), mutation operator, mutation scale

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