计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (1): 63-65.DOI: 10.3778/j.issn.1002-8331.2009.01.019

• 理论研究 • 上一篇    下一篇

最优化问题全局寻优的AFSA-BFGS混合算法

黄华娟,周永权   

  1. 广西民族大学 数学与计算机科学学院,南宁 530006
  • 收稿日期:2008-12-28 修回日期:2008-03-06 出版日期:2009-01-01 发布日期:2009-01-01
  • 通讯作者: 黄华娟

AFSA-BFGS hybrid algorithm of global optimum for optimization problems

HUANG Hua-juan,ZHOU Yong-quan   

  1. College of Math and Computer Science,Guangxi University for Nationalities,Nanning 530006,China
  • Received:2008-12-28 Revised:2008-03-06 Online:2009-01-01 Published:2009-01-01
  • Contact: HUANG Hua-juan

摘要: 针对人工鱼群算法在优化后期收敛速度变慢问题,利用BFGS算法快速的局部搜索能力来改进,提出了一种最优化问题全局寻优的AFSA-BFGS混合算法。通过8个标准函数测试结果表明,AFSA-BFGS混合算法,不仅具有全局收敛性能,而且还具有较快的收敛速度和更高的求解精度,是求解优化问题的一种有效方法。

关键词: 人工鱼群算法, 混合算法, BFGS算法, 全局最优化

Abstract: To overcome the problem of slow convergence on artificial fish school algorithm(AFSA),this paper proposes a hybrid algorithm of AFSA-BFGS using the quick local convergence of BFGS algorithm,eight practical functions are selected as the test function.The experimental results show that the AFSA-BFGS algorithm not only can effectively locate the global optimum,but also have a rather high convergence speed.The AFSA-BFGS algorithm is a promising approach for solving global optimization problems.

Key words: artificial fish school algorithm, hybrid algorithm, Broyden-Fletcher-Gddfarb-Shanno(BFGS) algorithm, global optimum