On the Dynamic Ant Colony Algorithm Optimization Based on Multi-pheromones

On the Dynamic Ant Colony Algorithm Optimization Based on Multi-pheromones
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DOI：
10.1109/icis.2008.112
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发表时间：
2008-05
期刊：
Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
影响因子：
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通讯作者：
Ya-mei Xia;Jun-Liang Chen;Xiang-wu Meng
Ya-mei Xia;Jun-Liang Chen;Xiang-wu Meng
中科院分区：
其他
文献类型：
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作者：
Ya-mei Xia;Jun-Liang Chen;Xiang-wu Meng

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本文提出了一种基于多信息素的动态蚁群优化算法DACO（dynamic ant colony optimization algorithm based on multi-pheromones），用于解决Web服务状态和服务质量的动态性问题。为了更准确地表示用户的需求，该算法设置了多个信息素。在实验的基础上对DACO算法进行了改进，使其更好更快地收敛到最优值。仿真实验表明，DACO算法比蚁群算法和遗传算法更有效地应用于服务组合。
In this paper, an algorithm DACO (dynamic ant colony optimization algorithm based on multi- pheromones) is put forward to apply to the dynamics of web services state and QoS in service composition optimization. In order to denote users' needs more accurately, this algorithm sets multiple pheromones. The DACO is also improved based on experiment in order to make it better and faster converge to optimization value. Simulation experiment in this paper shows that the DACO is more effective than Ant Colony Algorithm and a Genetic Algorithm applied to services composition.