文化蛙跳算法性能分析研究

Performance Analysis Research on Cultural and Shuffled Frog Leaping Algorithm

基本混合蛙跳算法收敛速度较慢,优化精度较低。为进一步提高混合蛙跳算法的优化速度和精度,将文化算法模型引入到混合蛙跳算法中,提出了一种文化蛙跳算法。利用混合蛙跳算法良好的全局协同搜索能力和文化算法模型中的遗传操作,提高了算法的收敛精度,增强了算法的群体多样性。通过对3个测试函数进行优化实验,并与文中文化蛙跳算法和相关文献中的改进算法进行比较,实验结果表明文中提出的改进文化蛙跳算法具有更好的优化性能。

The Shuffled Frog Leaping Algorithm （ SFLA） has slow convergence speed and low optimization precision. In order to further improve the optimization speed and precision of the SFLA,the improved Cultural And Shuffled Frog Leaping Algorithm （ CA-SFLA） is proposed,through introducing the cultural algorithm model into shuffled frog leaping algorithm. The new convergence precision is im-proved and the population diversity is enhanced,by using the outstanding global cooperative search ability of the shuffled frog leaping al-gorithm and the genetic operation of culture algorithm model. Through testing three benchmark functions,and compared with basic CA-SFLA and the improved CA-SFLA in related references,the results show that CA-SFLA proposed has better performance.