具有Lévy飞行和精英反向学习的果蝇优化算法

具有Lévy飞行和精英反向学习的果蝇优化算法
杨菊蜻;张达敏;张慕雪;朱陈柔玲
【期刊名称】《通信技术》
【年(卷),期】2017(050)009
【摘要】针对果蝇优化算法(FOA)寻优精度不高、容易陷入局部极值的缺陷,提出了一种具有莱维飞行搜索策略和精英反向学习的果蝇优化算法(LOBL-FOA).首先,采用莱维飞行搜索模式对果蝇寻优过程中位置更新方式进行改进,使得算法具有较强的全局寻优能力,并在一定程度上避免了算法的过早收敛;其次,对精英果蝇个体进行反向学习生成反向解,保留具有较优味道浓度的果蝇个体,从而提高了算法搜索精度;最后,对5个经典测试函数在固定迭代次数和固定寻优精度条件下进行仿真测试,并同参考文献算法进行对比,结果表明本文提出的改进果蝇优化算法相较于传统果蝇优化算法具有较强的寻优精度和收敛效率.%For the basic Fruit Fly Optimization Algorithm (FOA) has the shortcomings of low optimization precision and easily falling into local optimal value, a fruit fly optimization algorithm with Lévy flight and elite reverse learning (LO BL-FOA) is proposed. First of all, the Levy flight search mode is adopted to improve the location update way in fruit fly optimization process, thus making the algorithm with fairly strong global optimization ability and avoiding to a certain extent the premature convergence of the algorithm. Then the reverse learning of elite fruit fly individuals is used to generate inverse solutions, and the individual fruit flies with better taste concentration are retained, thus improving the searching accuracy of the algorithm. Finally,
the simulation tests of 5 classical test functions under the condition of fixed iteration and fixed optimization precision are carried out, and compared with the reference algorithm. The experiment results show that the modified fruit fly optimization algorithm has much stronger optimization precision and convergence efficiency than the traditional fruit fly optimization algorithms.
【总页数】7页(P1929-1935)
【作者】杨菊蜻;张达敏;张慕雪;朱陈柔玲
【作者单位】贵州大学大数据与信息工程学院,贵州贵阳 550025;贵州大学大数据与信息工程学院,贵州贵阳 550025;贵州大学大数据与信息工程学院,贵州贵阳550025;贵州大学大数据与信息工程学院,贵州贵阳 550025
【正文语种】中文
【中图分类】TP301.6
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