New Adaptive Control Strategies for Parameters of Genetic Algorithms

Adaptive control strategies for parameters of genetic algorithms can be built according to the heuristic rules or artificial intelligent techniques.A fuzzy adaptive genetic algorithm with variable population size(FAGAVPS) is proposed to overcome premature convergence and slow convergence speed at later evolution process of simple genetic algorithm.FAGAVPS uses both macroscopical and microscopical control based on heuristic rules to realize population size adaptation.The crossover rate and mutation rate of the algorithm are also tuned automatically in the evolutionary process by two fuzzy controllers with different characteristics.The experiments show that FAGAVPS can efficiently avoid premature convergence and the performance of genetic algorithm can be greatly raised by applying adaptive control strategies.