Optical thin film optimization design using genetic algorithms

Optical thin films are used in a wide variety of optical components. An important aspect of modern thin film design work is the use of computers to match the multilayer parameters to a set of optical specifications such as a desired reflectance curve. There are several basic approaches to the design of thin film multilayer coatings. These include graphical, analytical and digital design methods. The latter, representing both local and global minimum seeking algorithms, are particularly powerful because they lend themselves to the design of coatings with much more complicated properties than is possible with the other methods. Many traditional optimization techniques, including Simplex, Gradient, and Damped least squares method, have been used in this field. However, up to now, it has not been possible to say if one of these techniques gives the optimal solution of the problem to be solved. A genetic algorithm is introduced to search for the optimal optical thin film design. This paper discusses the problem of thin film design in greater detail. It shows how a genetic algorithm can evolve the design for better performance. Examples of designs obtained by GA optimization techniques are given