Classical and Evolutionary Algorithms in the Optimization of Optical Systems

The optimization of optical systems is a very old problem. As soon as lens designers discovered the possibility of designing optical systems, the desire to improve those systems by the means of optimization began. For a long time the optimization of optical systems was connected with well-known mathematical theories of optimization which gave good results, but required lens designers to have a strong knowledge about optimized optical systems. In recent years modern optimization methods have been developed that are not primarily based on the known mathematical theories of optimization, but rather on analogies with nature. While searching for successful optimization methods, scientists noticed that the method of organic evolution (well-known Darwinian theory of evolution) represented an optimal strategy of adaptation of living organisms to their changing environment. If the method of organic evolution was very successful in nature, the principles of the biological evolution could be applied to the problem of optimization of complex technical systems.

Inhalt
1 Introduction.- 2 Classical algorithms in the optimization of optical systems.- 3 Genetic algorithms.- 4 Evolution strategies.- 5 Comparison of optimization algorithms.- 6 Ray trace.- 7 Aberrations.- 8 Damped least squares optimization implementation.- 9 Adaptive steady-state genetic algorithm implementation.- 10 Two membered evolution strategy ES EVOL implementation.- 11 Multimembered evolution strategies ES GRUP and ES REKO implementation.- 12 Multimembered evolution strategy ES KORR implementation.- 13 The Cooke triplet optimizations.- 14 The Petzval objective optimizations.- 15 The Double Gauss objective optimizations.- 16 Summary and outlook.- Appendix A Description of ADOS the program for automatic design of optical systems.- Online bibliography.- References.