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 α. Effect of both these parameters on convergence is presented in this work for the proposed GA.