摘要
由于飞蛾扑火优化(MFO)算法收敛速度和计算精度还有待提高,提出一种改进的基于Lévy飞行轨迹的飞蛾扑火优化(LMFO)算法。增强局部搜索能力,大幅度提升收敛速度和求解精度。对12个无约束基准函数进行实验测试,测试结果表明,改进后的LMFO是有效可行的。
Moth-flame optimization （MFO） algorithm still in its infancy so far, the convergence speed and computation accuracy need to be improved. Therefore, an improved moth-flame optimization algorithm based on Levy flights trajectory, namely LMFO,was proposed. The local search ability was enhanced, its convergence speed and precision were greatly improved By means of testing 12 unconstrained benchmark functions？ the results demonstrate that LMFO is efficitive and feasible.
出处
《计算机工程与设计》
北大核心
2017年第3期807-813,共7页
Computer Engineering and Design
基金
国家自然科学基金项目(21466008)
关键词
最优化
横向定位
飞蛾扑火优化
Lévy飞行
精度
optimization
transverse orientation
moth-flame optimization
Lévy flights
accuracy
