智能系统学报Issue(3)：414-421,8.DOI:10.3969/j.issn.1673-4785.201405070
广义中心混合蛙跳算法
Shuffled frog-leaping algorithm based on the general center
摘要
Abstract
In this paper, a shuffled frog⁃leaping algorithm based on general center ( GC⁃SFLA) is proposed to solve the problem of weak information sharing between memeplexes in the shuffled frog leaping algorithm ( SFLA) to en⁃hance the learning ability and use the average center of optimal frog. The proposed GC⁃SFLA generates a virtual general center frog from the optimal frog of each memeplex. Firstly, the optimal frog selects the best location among the original location and general center greedily as new location of new memeplex. After that, the advantage of gen⁃eral center frog is applied to the frog⁃leaping rule, which enable the worst frog to learn from the general center frog. Experiments are conducted on a set of swarm intelligence algorithms to verify that the new approach outperforms SF⁃LA in different dimensions. The experiment results present promising performance of the GC⁃SFLA on convergence velocity, precision and stability of solution.关键词
蛙跳算法/混合蛙跳算法/广义中心/蛙跳规则/群智能算法Key words
frog-leaping algorithm/shuffled frog leaping algorithm ( SFLA )/general center/frog leaping rule/swarm intelligence algorithms分类
信息技术与安全科学引用本文复制引用
赵嘉,吕莉,樊棠怀..广义中心混合蛙跳算法[J].智能系统学报,2015,(3):414-421,8.基金项目
国家自然科学基金资助项目（61261039，61263029）；江西省自然科学基金资助项目（20132BAB211031）；江西省科技厅科技支撑项目（20142BBG70034）；南昌市科技计划项目（2013HZCG006，2013HZCG011，2014HZZC008）． （）
