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基于相对距离和关联度的多任务联盟的蚁群算法

Keywords: 多任务联盟问题,蚁群算法,相对距离,关联度,多Agent系统

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Abstract:

针对蚁群算法在求解多任务联盟问题(multi-taskcoalitionproblem,MTCP)时存在的迭代次数多、求解精度不高的问题,提出了一种基于相对距离和关联度的蚁群算法.该算法针对蚁群算法搜索机制和信息素增量模型,提出了2种策略.首先,为提高资源利用效率,减少Agent的能力浪费,引入了相对距离的概念,提出了基于相对距离的搜索机制;其次,为强化蚂蚁间的协作,利用已获得的解信息,给出了一种基于关联度的信息素增量模型.仿真实验结果表明,与已有的一些算法相比,本文算法不仅能获得更好的联盟结构,而且具有较快的收敛速度.

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