摘要
人工鱼群算法(AFSA)是一种高效的群智能全局优化技术。通过对人工鱼群算法(AFSA)不足的研究,在遗传算法的基础上,提出了基于遗传算法的人工鱼群优化算法。该算法保留了人工鱼群算法(AFSA)简单、易实现的特点,同时克服了人工鱼漫无目的的随机游动或在非全局极值点的大量聚集,显著提高了算法的运行效率和求解质量。最后通过大量的函数和实例测试结果表明,与其它算法相比,该算法是可行和有效的,具有运行速度快和求解精度高等特点。
Artificial fish swarm algorithm （AFSA） is an efficient intelligent optimization technique. The disadvantages of AFSA is researched, then a hybrid artificial fish swarm optimization algorithm based on genetic algorithm is presented. The hybrid algorithm break away from artificial fish moving without a definite purpose or heavy getting together round the local optimum. It is simple and im- plement as AFSA, but can greatly improve the ability of efficiency and accuracy of seeking the global excellent result. The feasibility and effectiveness of the approach is verified through testing by some functions and practical problems. Compared with the other algorithms, the experimental results show that the proposed algorithm has traits with quickly speed and high precision.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第22期5827-5829,共3页
Computer Engineering and Design
基金
国家自然科学基金项目(60461001)
广西自然科学基金项目(0542048)
关键词
人工鱼群算法
遗传算法
优化
artificial fish school algorithm
genetic algorithm
optimization
