Genetic Algorithm for More Efficient Multi-layer Thickness Optimization in Solar Cell

We propose to use Genetic Algorithm (GA), inspired by Darwin's evolution theory, to optimize the search for the optimal thickness in organic solar cell's layers with regards to maximizing the short-circuit current density. The conventional method used in optimization simulations, such as for optimizing the optical spacer layers' thicknesses, is the parameter sweep. Our experiments show that the introduction of GA results in a significantly faster and accurate search method when compared to brute-force parameter sweep method in both single and multi-layer optimization.