A New Modified Accurate Genetic Algorithm for Multivariable Systems

The A major problem in using mutation is how to choose the probability of mutation. The uncertain nature of this parameter is a disadvantage in general GA methods. There is a critical unknown value for P_mute. Choosing P_mute above the critical value lead to high and also constant accuracy and the number of iterations increase, while smaller P_mute values result low accuracy and fewer iterations. There are few values for this parameter that guarantee answer accuracy with low iteration. In order to soften this problem we propose the modified mutation method. The proposed method has two major advantages in compare with simple mutation; first Pmute in this method is replaced with two new parameters (P_Start and De_Rate) which alleviate the problem of P_mute tuning. Second the answer accuracy in this algorithm is high but not constant similar to simple mutation methods. The maximum value of five multivariable sample functions is computed using both general and the proposed methods. Two important parameters, convergence rate and answer accuracy, are considered as factors to compare these methods. Results confirm effectiveness and robustness of the proposed method against general method.