关键词: 蚁狮算法, 双重反馈, 时空混沌, 高斯变异

Abstract: The Antlion Optimization （ALO） algorithm with low convergence precision and easy to fall into the local optimizations, the characteristics of the antlions’ability and the population improvement rate as the double feedback information 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.

Key words: Antlion Optimization algorithm（ALO）, double feedback, spatiotemporal chaos, Gaussian mutation