不同混沌序列对全局最优解的搜索影响

Effect of different chaotic sequences on seeking overall optimal solution

通过对Logistic映射、立方映射和无限折叠映射进行了比较,并分析了他们的混沌特性,通过实验仿真和数据统计,发现后两种映射所产的混沌序列更均匀些,加快了搜索全局最优解的速度。而混沌优化算法在解决多极点的优化问题时能够体现出它的优势。通过对传统的优化算法和混沌优化算法进行比较,并应用于求解多极点的全局最优解,得出的结论是,在解决多极点的优化问题时,混沌优化算法明显优于传统的优化算法。

Logistic map, cube mapg and unlimited folded maps are compared in this paper and the their chaotic characteristics are analyzed. Through simulation and statistics, it is found that the last two maps generated more even chaotic sequences and quickened the search for global optimal solution. Traditional optimization algorithm can perfectly solve the optimization problem of unipolar. However, it is unsatisfactory for multi-polar. Chaotic optimization algorithm takes its advantages to resolve the problem. In this paper, the traditional and chaotic optimization algorithms are compared, and applied for resolving the multi-target extreme values. It is concluded that chaotic optimization algorithm is superior to the traditional one.