【摘要】 针对简单遗传算法(SGA)存在早熟和易陷入局部最优的不足,提出了一种新的动态调整交叉概率和变异概率的自适应遗传算法(AGA),同时对简单遗传算法的编码方式、选择、交叉和变异算子均进行了一定的改进。通过对一复杂函数———Schaffer函数进行求解,证明了这些改进措施有效地克服了早熟现象、提高了算法的全局寻优能力。并利用改进的自适应遗传算法对水电站报价策略模型进行求解,结果表明了该方法的有效性。更多还原

【Abstract】 Aiming at the shortcoming that the simple genetic algorithm(SGA) is difficult to deal with premature and local convergence,this paper puts forward a novel adaptive genetic algorithm(AGA) that adaptively adjusts the crossover and mutation probability,and makes improvement on the coding mode、selection、crossover and mutation operators.The proposed algorithm is tested with a complex mathematics function——Schaffer function,and the experimental results show that the algorithm have effectively overcome the premature and improved the ability to converge to the global optimum.The modified adaptive genetic algorithm is applid to solve the bidding strategy model for hydropower plants,and the results show that this approach is valid.更多还原