摘要
为综合解决传统烟花算法爆炸半径可能为零导致资源浪费以及增强烟花算法引入的最小爆炸半径检测机制导致局部搜索能力较弱的问题,针对增强烟花算法提出了两种改进策略:引入自适应动态半径调整策略改进爆炸半径,根据不同阶段的启发式信息,即当前最优烟花距离其他烟花位置的信息,动态调整爆炸半径的大小来平衡全局和局部搜索能力,该策略可以使算法后期爆炸半径缩小到较小值进行细致的局部搜索;引入具有较强随机性的莱维飞行策略改进爆炸产生火花位置的方式,增强局部搜索的多样性。采用12个标准测试函数及其偏移函数进行实验,相比增强烟花算法,改进后的算法提高了标准函数及其偏移函数的寻优精度,在高维复杂的优化问题上具有较好的收敛能力。
In order to solve the problem of the waste of resources due to the small explosion amplitude with best fitness(even close to 0)in the conventional fireworks algorithm(FWA)and the problem of the relatively weak local search ability owing to the novel minimal explosion amplitude check method used in enhanced fireworks algorithm(EFWA),this paper provided two strategies to improve the performance of the EFWA.Firstly,it introduced an adaptive dynamic explosion amplitude update strategy based on the heuristic information of distance between the current best firework and other fireworks to balance the glo-bal and local search of the EFWA.And then,it used Lévy flight strategy with strong randomness to generate explosion sparks to enhance the diversity of local search.The experimental results on twelve standard benchmark functions and their shifted functions indicate that the proposed algorithm outperforms EFWA in terms of optimization accuracy and convergence abilities on complex high-dimension optimization.
作者
段娇娇
曲强
高闯
陈雪波
Duan Jiaojiao;Qu Qiang;Gao Chuang;Chen Xuebo(School of Electronic&Information Engineering,University of Science&Technology Liaoning,Anshan Liaoning 114051,China)
出处
《计算机应用研究》
CSCD
北大核心
2018年第10期3011-3015,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(71371092)
辽宁科技大学研究生教育改革与科技创新创业项目(LKDYC201605)
关键词
增强烟花算法
烟花算法
自适应动态爆炸半径
莱维飞行
enhanced fireworks algorithm
fireworks algorithm
adaptive dynamic explosion amplitude
Lévy flight