Antlion Optimization Algorithm Based on Quadratic Interpolation

Wen-yan GUO, Ke-xin LIU, Xuan ZHANG, Jiao-jiao ZHANG


Because of slow convergence speed and low calculation precision of antlion optimization (ALO) algorithm, an improved algorithm named quadratic interpolation antlion optimization (QIALO) is put forward in this paper puts. The new algorithm uses the quadratic interpolation (QI) to obtain the secondary renewal position of ants, which enhances the local search ability of the antlion optimization algorithm and accelerates the global optimization speed of the population. Simulation results on thirteen test functions indicate that the performance of the new algorithm is better than that of the contrast algorithms in the statistical sense, and the performance of QIALO algorithm for multimodal optimization is improved effectively.


Quadratic interpolation, Antlion optimization algorithm, Computational intelligence, Swarm intelligence.


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