计算机工程与应用2018，Vol.54Issue(1)：179-185,7.DOI:10.3778/j.issn.1002-8331.1607-0192
反向自适应高斯变异的人工鱼群算法
Opposite adaptive and Gauss mutation artificial fish swarm algorithm
摘要
Abstract
The Artificial Fish Swarm Algorithm(CAFSA)has some disadvantages such as falling into local optimum, poor robustness and low search accuracy. To solve these problems, this paper proposes an opposite adaptive and Gauss mutation artificial fish swarm algorithm. To provide more opportunities to explore potential better area, the algorithm applies opposite point to adjust direction and location of artificial fish. Thereby, the algorithm can jump out of local optimum fast and improve better global searching ability. In addition, this algorithm balances the global and local searching ability by using a non-linear function to adjust artificial fish's visual and step. Otherwise, in order to solve early-maturing of artificial fish, using Gauss mutation mechanism based on optimal solution increases the diversity of every artificial fish. The simulation results show that improved artificial fish swarm algorithm has good searching quality, better accuracy and robustness. Meanwhile, the algorithm avoids early-maturing compared with other AFSAs.关键词
人工鱼群算法/自适应/高斯变异/反向解Key words
Artificial Fish Swarm Algorithm(AFSA)/adaptive/Gauss Mutation(GM)/opposite point分类
信息技术与安全科学引用本文复制引用
姚凌波,戴月明,王艳..反向自适应高斯变异的人工鱼群算法[J].计算机工程与应用,2018,54(1):179-185,7.基金项目
国家高技术研究发展计划(863)(No.2014AA041505) （863）
国家自然科学基金(No.61572238). （No.61572238）
