Box-complex assisted genetic algorithm for optimal control of batch reactor

To enhance convergence property of Genetic Algorithm (GA), we in this work propose modification in GA by combining the global search property of GA with a convergence property of Box-Complex method. Using the current population of GA, new members are created using Box-Complex concept, which replaces equal number of worst population members. A comparative study of the proposed GA with the conventional GA and widely accepted Jumping Gene GA (JG GA) is presented in this work. We have considered two mathematical and a batch reactor optimal control applications for evaluating the efficacy of the proposed GA. There are two user defined parameters in the proposed algorithm, namely extent of Box-Complex Assistance(BCA), and expansion/contraction factor. Effect of both these parameters on convergence is presented in this work for the proposed GA.