Efficient evolutionary algorithm for the thin-film synthesis of inhomogeneous optical coatings

We propose an efficient evolutionary approach for the thin-film synthesis of inhomogeneous optical coatings. The proposed approach consists of global and local strategies by integration of decreasing-based mutations and self-adaptive mutations by means of family competition and adaptive rules. Numerical results indicate that the proposed approach performs robustly and is competitive with other approaches. Our approach, although somewhat slower, is flexible and can easily be adopted to other application domains. Our approach is also able to generate homogeneous solutions with two materials available.