Based on the initial value sensitivity of chaotic motion and the analysis of optimal searching process, a parallel adaptive chaotic optimization (PACO) method is proposed.
基于混沌运动的初值敏感性和对混沌优化搜索过程的分析，提出了并行自适应混沌优化方法。
The proposed adaptive optimization method has been validated using several analytic function tests. Numerical results show that the algorithm has the property of fast global searching.
利用解析函数对上述自适应优化方法进行了验证，算例结果证明了该算法的全局搜索和快速寻优能力。
应用推荐