计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (27): 53-57.

• 研究、探讨 • 上一篇    下一篇

学习猴群爬过程的人工蜂群优化算法

贾瑞民1,何登旭2,石绍堂1   

  1. 1.广西民族大学 信息科学与工程学院,南宁 530006
    2.广西民族大学 东盟学院,南宁 530006
  • 出版日期:2012-09-21 发布日期:2012-09-24

Artificial Bee Colony optimization algorithm studying climb process of Monkey Algorithm

JIA Ruimin1, HE Dengxu2, SHI Shaotang1   

  1. 1.College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China
    2.College of Association of Southeast Asian Nations, Guangxi University for Nationalities, Nanning 530006, China
  • Online:2012-09-21 Published:2012-09-24

摘要: 针对人工蜂群算法迭代后期容易陷入局部的缺点,将猴群算法的爬过程引入到采蜜蜂采蜜的阶段,加强局部搜索。通过仿真实验测试,与参考文献中的改进算法进行比较,可以得到提出的改进算法比原人工蜂群算法及现有的部分改进算法性能优良,能够在一定程度上跳出局部最优,得到的近似解也更加接近测试函数理论最优解。

关键词: 人工蜂群算法, 猴群算法, 爬过程, 局部搜索

Abstract: An improved Artificial Bee Colony(ABC) algorithm is proposed to overcome the flaw of standard ABC by introducing the climb process of Monkey Algorithm to update food source in order to enhance the local search ability at the stage of employ bees. Simulation results show that the proposed algorithm has better performance than ABC and the other kinds of improved algorithms put forward literally. It can jump out of local optima in a certain extent and get approximate solutions which are much closer to the theoretical solutions of the test functions.

Key words: Artificial Bee Colony algorithm(ABC), Monkey Algorithm, climb process, local search