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计算机工程 ›› 2007, Vol. 33 ›› Issue (23): 199-201. doi: 10.3969/j.issn.1000-3428.2007.23.069

• 人工智能及识别技术 • 上一篇    下一篇

多蚁群伪并行优化算法

刘利强1,袁赣南1,戴运桃2   

  1. (1. 哈尔滨工程大学自动化学院,哈尔滨 150001;2. 哈尔滨工程大学理学院,哈尔滨 150001)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-05 发布日期:2007-12-05

Multi-ant Colony Virtual Parallel Optimization Algorithm

LIU Li-qiang1, YUAN Gan-nan1, DAI Yun-tao2   

  1. (1. College of Automation, Harbin Engineering University, Harbin 150001; 2. College of Sciences, Harbin Engineering University, Harbin 150001)
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-05 Published:2007-12-05

摘要: 针对传统蚁群算法容易出现早熟和停滞现象,提出了一种多蚁群伪并行优化算法,将蚁群分成若干个子蚁群,在各子蚁群中引入信息素平滑机制,通过设计迁移算子,使多个子蚁群并行、协同寻优,从而使算法跳离局部最优解。类比实验表明,该算法比传统的蚁群算法具有更好的搜索全局最优解的能力。

关键词: 蚁群算法, 信息素平滑, 迁移算子, 多蚁群

Abstract: To overcome the limitation of precocity and stagnation in classical ant colony algorithm, this paper presents a multi-ant colony virtual parallel optimization algorithm. The ant colony is divided into several children ant colonies, and the pheromone flatness system is used in each child ant colony. By designing an immigrant operator, the parallel and cooperating optimization of children ant colonies ate obtained. Contrastive experiments show that the algorithm has a better capability of global optimization than traditional ant colony algorithm.

Key words: ant colony algorithm, pheromone flatness, immigrant operator, multi-ant colony

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