An Alternative Approach for PDE-Constrained Optimization via Genetic Algorithm

This paper deals with an alternative approach for solving the PDE-constrained optimization problems. For this purpose, the problem has been discretized with the help of finite difference method. Then the reduced problem has been solved by advanced real coded genetic algorithm with ranking selection, whole-arithmetic crossover and non uniform mutation. The proposed approach has been illustrated with a numerical example. Finally, to test the performance of the algorithm, sensitivity analyses have been performed on objective function values with respect to different parameters of genetic algorithm.