摘要
针对已有的混沌优化算法几乎都是利用Logistic映射作为混沌序列发生器,而该混沌序列的概率密度函数呈两头多、中间少的切比雪夫型的分布性质,不利于搜索的效率和能力,为此,首先构造一种新型混沌映射序列发生器—Skew Tent映射并结合迭代优化特点加以改进,然后分析了它的混沌特性．其次,将改进的混沌映射与Alopex启发算法相结合,充分发挥Alopex算法的快速搜索能力和混沌优化全局寻优的特性,提出一种混沌混合优化算法,提高了算法的收敛速度和有效搜索全局最优解．最后,仿真算例验证了该算法的有效性和Skew Tent混沌映射的应用前景．
The existing chaos optimization algorithms were almost based on Logistic map. However, the probability density function of chaotic sequences for Logistic map is a Chebyshev-type function, which may affect the global searching capacity and computational efficiency of chaos optimization algorithm. Firstly, a new chaotic sequences-Skew Tent map is established in this paper, and is improved by its iterative optimization property. The chaotic performance of Skew Tent map is then discussed by eliminating the bad points during the chaos searching. A hybrid optimization algorithm, in which the improved chaotic map is combined with the Alopex heuristic algorithm, is also proposed by making full use of the properties of the rapid search capability of Alopex algorithm and the global optimization of improved chaotic map. The convergence speed and global optimal value of the presented algorithm are thus improved. Finally, the simulation examples show the effectiveness of the algorithm, as well as the practicability of Skew Tent map.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2007年第2期269-273,共5页
Control Theory & Applications
基金
安徽省教育厅自然科学基金(2006KJ080B)
安徽省教育厅杰出青年基金(2005jq1119)
