Robust design of multilayer optical coatings by means of evolutionary algorithms

Robustness is an important requirement for almost all kinds of products. This article shows how evolutionary algorithms can be applied for robust design based on the approach of Taguchi. To achieve a better understanding of the consequences of this approach, we first present some analytical results gained from a toy problem. As a nontrivial industrial application we consider the design of multilayer optical coatings (MOCs) most frequently used for optical filters. An evolutionary algorithm based on a parallel diffusion model and extended for mixed-integer optimization was able to compete with or even outperform traditional methods of robust MOC design. With respect to chromaticity, the MOC designs found by the evolutionary algorithm are substantially more robust to parameter variations than a reference design and therefore perform much better in the average case. In most cases, however, this advantage has to be paid for by a reduction in the average reflectance. The robust design approach outlined in this paper should be easily adopted to other application domains.

[1]  Horst Greiner Robust filter design by stochastic optimization , 1994, Other Conferences.

[2]  Robert G. Reynolds,et al.  Evolution Strategies for Mixed-Integer Optimization of Optical Multilayer Systems , 1995 .

[3]  Shigeyoshi Tsutsui,et al.  Genetic algorithms with a robust solution searching scheme , 1997, IEEE Trans. Evol. Comput..

[4]  T. R. Bement,et al.  Taguchi techniques for quality engineering , 1995 .

[5]  Hans-Georg Beyer,et al.  Toward a Theory of Evolution Strategies: Some Asymptotical Results from the (1,+ )-Theory , 1993, Evolutionary Computation.

[6]  Reinhard Herrmann,et al.  Design and manufacturing of ophthalmic antireflection coatings with low angular color shift , 1990, Other Conferences.

[7]  Thomas Bäck,et al.  Evolution strategies applied to perturbed objective functions , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[8]  Thomas Bäck,et al.  Evolution Strategies for Mixed-Integer Optimization of Optical Multilayer Systems , 1995, Evolutionary Programming.

[9]  Martin Schütz,et al.  Application of Parallel Mixed-Integer Evolution Strategies with Mutation Rate Pooling , 1996, Evolutionary Programming.

[10]  Shigeyoshi Tsutsui,et al.  A Robust Solution Searching Scheme in Genetic Search , 1996, PPSN.

[11]  S Martin,et al.  Synthesis of optical multilayer systems using genetic algorithms. , 1995, Applied optics.

[12]  H. Greiner Robust optical coating design with evolutionary strategies. , 1996, Applied optics.