摘要
针对蛙跳算法(SFLA)前期搜索速度慢且易陷入局部最优的不足,提出一种人工鱼群-蛙跳混合优化算法(AFSA-SFLA)。算法结合人工鱼群算法(AFSA)前期收敛速度快和SFLA局部搜索能力强的优势,提高了青蛙种群的质量。选取典型测试函数进行测试,测试结果验证了人工鱼群-蛙跳混合优化算法的有效性和优越性。
Due to the defects that the shuffled frog leaping algorithm(SFLA) has a slow convergence speed and is easy to fall into the local convergence, a hybrid artificial fish swarm and shuffled frog leaping algorithm(AFSA-SFLA) is proposed. This algorithm combines the advantages of the fast convergence speed in the early stage of the artificial fish swarm algorithm(AFSA) and the local search ability of the SFLA, which improves the quality of the frog population. Tests are conducted by appropriate functions for the verification. The results show the effectiveness and efficacy of the hybrid AFSA-SFLA.
作者
姜慧楠
张向锋
JIANG Huinan;ZHANG Xiangfeng(School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China)
出处
《上海电机学院学报》
2019年第6期330-336,344,共8页
Journal of Shanghai Dianji University
基金
国家自然科学基金青年基金项目(61803253)
关键词
人工鱼群算法
蛙跳算法
人工鱼群-蛙跳混合优化算法
artificial fish swarm algorithm(AFSA)
shuffled frog leaping algorithm(SFLA)
artificial fish swarm and frog leaping algorithm(AFSA-SFLA)
