蚁群的新计算模型

Wei Gao
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引用次数: 14

摘要

生命系统的计算模型已经成为一种主要的智能算法。蚁群算法是一种模拟蚁群行为的群体智能的新型计算模型。这是一种很好的组合优化方法。为了扩展蚁群算法,提出了一些连续蚁群算法。为了提高搜索性能,将进化算法和免疫系统的原理与典型的连续蚁群算法相结合,提出了一种新的计算模型。在该模型中,蚂蚁个体通过自适应Cauchi突变和厚度选择进行转化。为了验证新的计算模型,采用了典型函数,如Schaffer函数。然后,将新算法与蚁群算法和免疫进化规划算法的结果进行了比较。结果表明,新算法的收敛速度和计算精度都很好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Computational Model from Ant Colony
The computational model from life system has become a main intelligent algorithm. Ant colony algorithm is a new computational model from mimic the swarm intelligence of ant colony behavior. And it is a very good combination optimization method. To extend the ant colony algorithm, some continuous ant colony algorithms have been proposed. To improve the searching performance, the principles of evolutionary algorithm and immune system have been combined with the typical continuous ant colony algorithm, and one new computational model is proposed here. In this new model, the ant individual is transformed by adaptive Cauchi mutation and thickness selection. To verify the new computational model, the typical functions, such as Schaffer function is used. And then, the results of new algorithm are compared with that of ant colony algorithm and immunized evolutionary programming which is proposed by author. The results show that, the convergent speed and computing precision of new algorithm are all very good.
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