摘要
针对基本捕鱼策略优化算法(FSOA)在优化过程中存在易陷入局部最优、求解高维的复杂优化问题时优化性能不好的不足,对基本捕鱼策略优化算法(FSOA)进行了改进,提出了自调整的捕鱼策略优化算法(ADFSOA):算法采用时变的搜索半径,每个渔夫可根据自己所处的状态自我调整搜索策略。通过与基本FSOA、RFSOA和标准PSO算法的数值实验对比,表明了所提算法的优化性能具有显著的优势,可用于求解高维的复杂优化问题。
In order to overcome the shortcomings that basic FSOA is easily trapped in local optimum and unable to solve the high-dimensional complex optimization problems, an improved FSOA, named AD- j ustive Fishing Strategy Optimization Algorithm （ADFSOA）,is proposed. In the algorithm, every fisher- man （searcher） uses a time-varying search-radius and can adjust his searching strategy according to his own state. Numerical experiments show that, compared with basic FSOA, RFSOA and standard PSO, the proposed algorithm is much superior to other algorithms and can be used to solve the complex high-dimensional optimization problems.
出处
《计算机工程与科学》
CSCD
北大核心
2014年第5期923-929,共7页
Computer Engineering & Science
基金
国家自然科学基金资助项目(61074185)
广西自然科学基金资助项目(0832084)
广西高等学校科研项目(201202ZD032)
