Ant lion optimization algorithm based on cauchy variation

In order to solve these problems that the ant lion optimization algorithm(ALO) is easy to fall into the local optimal stagnation, convergence precision is low and convergence speed is slow, an ant lion optimization algorithm based on cauchy variation is proposed. The adaptive t-distribution of cauchy variation is incorporated into the ant lion optimization algorithm to improve the effective. The elite ant lion individuals were selected by roulette to improve the adaptability of the ant lion population and the overall optimization efficiency of the population. The adaptive cauchy mutation operator makes the individual of the ant lion less constrained of the local extreme point, makes the search jump out of the local optimum quickly, and greatly improves the global search ability and convergence speed. Function test experiments were carried out on CALO, ALO, FPA and BA algorithms through 9 standard test functions of single mode and multi-mode. The simulation results show that the improved algorithm proposed in this paper is feasible and has better convergence speed and optimization precision.