基于文化的连续蚂蚁优化算法的研究  

Research on cultural continuous ant colony optimization algorithm

作　　者：马卫[1] 朱娴[1] 朱庆保[1] 

机构地区：[1]南京师范大学数学与计算机科学学院,南京210097

出　　处：《计算机应用研究》2009年第7期2442-2445,2449,共5页Application Research of Computers

基　　金：国家自然科学基金资助项目(60673102);江苏省自然科学基金资助项目(BK2006218)

摘　　要：针对蚂蚁优化算法在求解连续空间问题方面的缺陷,提出一种基于文化的连续蚂蚁优化算法。该算法将蚂蚁优化算法纳入文化算法的框架,组成基于蚂蚁优化算法的主群体和信念的两大空间。在知识和群体层面使用双重进化机制支持问题的求解和知识的提取,从而充分利用精英蚂蚁所携带的特征信息,在很大程度上提高了收敛速度,增强了搜索的多样性。实验结果表明,该算法求解速度快、寻优成功率高,是一种提高蚂蚁优化算法性能的有效算法。In order to deal with the continuous optimization problems that exist in the ant colony optimization algorithm, this paper proposed a continuous ant colony optimization algorithm based on cultural algorithm （CCACO）. This algorithm embedded ACO into the cultural algorithm framework and composed an algorithm with ACO main population space and belief space. Adopted doubleevolutionary mechanism is by knowledge and colony support to solve problem and extract knowledge. It is im- portant to make full use of characteristic information carried by elite ants, which not only increasing the speed of convergenee but also reinforcing the diversity of solution to a great extent. The results show that the algorithm is the effectiveness of the algorithm that improve the performance of ant colony optimization algorithm, increase the speed of resolution and advance the success rate for optimization.

关 键 词：函数优化 连续蚁群算法 文化蚂蚁优化算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]