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一种基于选择策略的差分混合蛙跳算法
引用本文:王林,万小雨,万建超.一种基于选择策略的差分混合蛙跳算法[J].计算机工程与科学,2018,40(1):121-127.
作者姓名:王林  万小雨  万建超
作者单位:(1.华中科技大学管理学院,湖北 武汉 430074;2.普天信息技术有限公司,北京 100080)
基金项目:国家自然科学基金(71602015,71531009);教育部人文社科规划项目(15YJA630095)
摘    要:设计了一种选择差分混合蛙跳算法SDSFLA,该算法通过增加组内个体更新个数提高了种群更新效率;通过引入差分进化算法的交叉算子和变异算子,加强了个体之间的信息交流;使用多种更新策略,提高了实验个体产生的成功率;随机选择控制参数,增加了种群的多样性。基于16个基准测试函数,将SDSFLA与一种改进的蛙跳算法、两种改进的差分进化算法进行对比,实验结果证实了SDSFLA算法的有效性和稳定性。

关 键 词:混合蛙跳算法  差分进化  实验个体选择  资源池  
收稿时间:2016-08-17
修稿时间:2018-01-25

A hybrid differential shuffled frog leaping algorithm based on selection strategy
WANG Lin,WAN Xiao-yu,WAN Jian-chao.A hybrid differential shuffled frog leaping algorithm based on selection strategy[J].Computer Engineering & Science,2018,40(1):121-127.
Authors:WANG Lin  WAN Xiao-yu  WAN Jian-chao
Affiliation:(1.School of Management,Huazhong University of Science and Technology,Wuhan 430074; 2.Potevio Information Technology Co. Ltd.,Beijing 100080,China)  
Abstract:A Selected Differential Shuffled Frog Leaping Algorithm (SDSFLA) is proposed. Compared with the classic Shuffled Frog Leaping Algorithm (SFLA), SDSFLA improves the efficiency of populationupdatingby increasingthe number of updated vectors, uses thecrossover operator and mutation operator of Differential Evolution(DE) to strengthen information exchanges between vectors, uses multiple updating strategies to improve the success rate of the trial vectors, and increases the diversity of the population viarandomly-selected control parameters.Based on 16 benchmark functions, SDSFLA is compared with an improved frog leaping algorithm and two improved differential evolution algorithms. The test results confirm the validity and stability of the SDSFLA algorithm.
Keywords:shuffled frog leaping algorithm  differential evolution  trial vector selection  resource pool  
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