计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (3): 9-12.DOI: 10.3778/j.issn.1002-8331.2010.03.003

• 博士论坛 • 上一篇    下一篇

混合多智能体遗传算法

潘晓英   

  1. 西安邮电学院 计算机系,西安 710121
  • 收稿日期:2009-09-28 修回日期:2009-11-20 出版日期:2010-01-21 发布日期:2010-01-21
  • 通讯作者: 潘晓英

Hybrid Multi-Agent Genetic Algorithm for numerical optimization

PAN Xiao-ying   

  1. Department of Computer Science and Technology,Xi’an University of Post & Telecommunications,Xi’an 710121,China
  • Received:2009-09-28 Revised:2009-11-20 Online:2010-01-21 Published:2010-01-21
  • Contact: PAN Xiao-ying

摘要: 综合多智能体的局部感知能力和遗传算法的强搜索能力,提出了一种混合多智能体遗传算法(HMAGA)。该方法构造了启发式搜索和混合交叉策略完成智能体之间的竞争和合作,综合凸变异和局部搜索体现智能体的自学习特性,通过智能体之间的相互作用来达到信息扩散的目的,最终收敛到全局最优解。在多组不同类型函数上的仿真实验结果表明,该算法具有良好的性能,特别是对于复杂的合成函数。

关键词: 多智能体系统, 启发式搜索, 混合交叉策略, 凸变异

Abstract: By integrated with the local apperceive ability of multi-agent system and the strong search ability of genetic algorithm,a Hybrid Multi-Agent Genetic Algorithm(HMAGA) is proposed.It constructs heuristic search and a hybrid crossover strategy to complete the competition and cooperation of agents,a convex mutation operator and some local search to achieve the self-learning characteristic.Some different type of testing functions proved the effectiveness of this algorithm.The experimental results show that HMAGA has a good performance on numerical optimization,especially for the composition functions.

Key words: multi-agent system, heuristic search, hybrid crossover strategy, convex mutation

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