[关键词]
[摘要]
针对现有遗传蚁群算法中算法融合不佳与系统易出现拥塞现象等问题,根据遗传算法与蚁群算法不同时期的优点,提出了一种高效的遗传蚁群组合算法。该算法通过根据遗传算法的群体代价关系,提出了新的融合机制;为缓解系统最优化后所产生的节点负载压力,引入了防拥塞的赏罚机制。实验结果表明,该算法能够在保证系统传输效率的同时有效的防止数据丢包现象,与传统算法相比具有高效率、低耗能以及防丢包等优势。
[Key word]
[Abstract]
Existing genetic ant colony algorithm has the problem of poor integration and prone to congestion. In response to this phenomenon, this article put forward an efficient combination of genetic ant colony algorithm based on the advantages of different periods of the genetic algorithm and ant colony algorithm. The algorithm proposes a new fusion mechanism on the basis of the consideration relationship of the genetic algorithm groups. And an anti-congestion reward and punishment mechanism is introduced to alleviate the load pressure of the system nodes. The experimental results show that the algorithm can guarantee the efficiency of the system transmission, at the same time it can effectively prevent data packet loss. Compared with the traditional algorithm, it has the advantages of high efficiency, low energy and anti-dropout.
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