自适应调整参数的果蝇优化算法
韩俊英;刘成忠
【期刊名称】《计算机工程与应用》 【年(卷),期】2014(000)007
【摘要】针对基本果蝇优化算法因参数选取不当而导致的收敛精度偏低且不稳定的问题，提出了自适应调整参数的果蝇优化算法（FOA with Adaptive Parameter，FOAAP）。该算法在每个进化代输入描述种群整体特征的精确数值，由逆向云发生器算法得到当代云模型的3个数字特征C(Ext'Ent'Het)，按照U 条件隶属云发生器自适应调整果蝇个体搜寻食物的方向与距离Value这一参数。将该算法在函数优化中，与基本果蝇优化算法以及相关文献中算法进行仿真对比，结果表明，新算法在收敛速度、收敛可靠性及收敛精度方面具有明显优势。%In order to overcome the problems of FOA, such as low convergence precision and unstable convergence resulted from improper random parameter, an improved FOA is proposed, called Fruit Fly Optimization Algorithm with Adaptive Parameter(FOAAP). In each evolutionary
generation,
the
accurate
values
describing
the
characteristics of the overall species are input, 3 digital characteristics C(Ext'Ent'Het) of the contemporary cloud model are obtained by backward cloud generator, then using U conditions membership cloud generator, the parameter Value is adaptively adjusted, which is Fruit Fly’s searching distance and direction for food. FOAAP is compared with FOA and other algorithms in reference literatures, experimental
自适应调整参数的果蝇优化算法
