计算机工程与应用2017，Vol.53Issue(12)：31-35,75,6.DOI:10.3778/j.issn.1002-8331.1703-0387
双重反馈机制的蚁狮算法
Antlion optimization algorithm based on double feedback mecha-nism
摘要
Abstract
The Antlion Optimization(ALO)algorithm with low convergence precision and easy to fall into the local opti-mizations, the characteristics of the antlions'ability and the population improvement rate as the double feedback informa-tion are introduced into the ALO algorithm , so the ALO algorithm based on Double Feedback mechanism(DFALO)is proposed. DFALO algorithm uses dynamic adaptive feedback as adjustment strategy to dynamically adjust the trap size to improve the convergence accuracy. Using spatiotemporal chaos exploration strategy to improve the global search ability, to avoid the algorithm into the local optimal. Using diversity feedback Gaussian mutation strategy to enhance the diversity of the population to avoid the algorithm precocious. Experimental results on eight standard test functions indicate that DFALO has a significant improvement in balance exploration and exploitation, high speed of convergence, strong global search ability and high precision.关键词
蚁狮算法/双重反馈/时空混沌/高斯变异Key words
Antlion Optimization algorithm(ALO)/double feedback/spatiotemporal chaos/Gaussian mutation分类
信息技术与安全科学引用本文复制引用
吴伟民,张晶晶,林志毅,苏庆..双重反馈机制的蚁狮算法[J].计算机工程与应用,2017,53(12):31-35,75,6.基金项目
国家自然科学基金(No.61273118) （No.61273118）
广东省科技计划(No.2016A010101027,No.2013B022200004) （No.2016A010101027,No.2013B022200004）
广州市科技计划(No.201605101034176). （No.201605101034176）
