Adaptive genetic algorithm based on hormone regulation

An improved adaptive genetic algorithm is proposed based on the principle of hormone modulation in endocrine system. An adaptive crossover operator and an adaptive mutation operator based on the downward form of Hill function are designed in the algorithm. The crossover rate and mutation rate are made self-regulated according to the standard deviation of fitness value in each generation. And the diversity is maintained at a reasonable level in the whole process of evolution to ensure the normal evolution of genetic algorithm. Experimental results of four test functions and 3D brain image segmentation show the improved genetic algorithm can maintain the diversity of the population effectively, and overcome the premature problem. The performances of the algorithm are better than those of the other three adaptive genetic algorithms and the traditional genetic algorithm.