Improved genetic algorithm based on population diversity and its application
基于种群相异度的改进遗传算法及应用

Based on population diversity, an improved genetic algorithm(IGA) was presented. The heuristic crossover strategy was adopted. In addition, the crossover scale, mutation scale and the mutation rate of each gene in each mutation individual could be adaptively adjusted according to the population diversity. Consequently, premature convergence was avoided and evolution was accelerated. IGA was applied into PID controller parameters optimization. Compared with traditional genetic algorithm(TGA), the simulation results prove that IGA is more efficient.