Evolutionary algorithms applied to lens design: case study and analysis

Lens system design makes extensive use of optimization techniques to improve the performance of an optical system. We know that designing a lens system is a complex task currently done by experienced optical designers, using specialized optical design software tools. In order to contribute to this particular field, this paper presents a comparison between lens design done by optical designers and evolutionary algorithms lens based design. Evolutionary algorithms consist in population-based global search methods inspired by natural evolution. They are recognized to be particularly efficient for complex non-linear optimization problems. Given the non-linear nature of lens design as an optimization process, evolutionary algorithms are good candidates for automating this task. The evolutionary algorithms were applied to the monochromatic quartet that was presented to expert participants at the International Lens Design Conference in 1990 (a friendly competition). Comparative results demonstrate that the evolutionary approach is able to find solutions slightly better than those presented at the competition. Then a real-life imaging problem is tackled. Results show that an evolutionary algorithm is again able to discover lens systems comparable to design done after a reasonable effort by experts. This paper presents an analysis of this approach for automatic lens design from a real-life optical design point of view.