计算机科学 ›› 2011, Vol. 38 ›› Issue (Z10): 268-270.

• 分布式与网络应用 • 上一篇    下一篇

基于混合遗传蚁群算法的多Agent动态任务分配研究

张晋,曹耀钦   

  1. (第二炮兵工程学院 西安 710025)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Research on Dynamic Task Allocation for MAS Based on Hybrid Genetic and Ant Colony Algorithm

ZHANG Jin, LAO Yao-qin   

  • Online:2018-11-16 Published:2018-11-16

摘要: 在多Agent系统中,由于任务的复杂性和!}gcnt之间的异构,Agent的动态任务分配问题实际上是一个NP难优化问题。针对MAS的任务分配问题的动态特性,首先建立任务分配数学模型,建立任务分配优化的目标函数;其次提出了一种混合遗传蚁群算法。利用遗传算法快速迭代和蚁群算法正反馈信息、分布式求解的特点实现任务分配的组合优化。实验仿真的结果分析表明,该算法具备较好的全局收敛效率和求解精度,可明显提升多Agcnt系统的性能。

关键词: 多Agcnt系统(MAS),动态任务分配,混合遗传蚁群算法

Abstract: In multi agent systems(MAS),because of the complexity and the difference between respective agents, the dynamic task allocation for multi agent systems is a NP-hard combinatorial optimization problem. According to the dy- namic characteristic of task allocation, first this paper established the mathematical model of task allocation and the target function. And then the hybrid genetic and ant colony algorithm which possesses the trait such as rapid iteration,poshive reaction and distribution, was put forward to achieve combinatorial optimization of task allocation. Finally, the simulation experiments demonstrated that, the algorithm is accomplished in convergence efficiency and solution precision can significantly enhance the performance of MAS.

Key words: MAS,Dynamic task allocation,Hybrid genetic and ant colony algorithm

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