Aspherical lens design using hybrid neural-genetic algorithm of contact lenses.

Abstract

The design of complex contact lenses involves numerous uncertain variables. How to help an optical designer to first design the optimal contact lens to reduce discomfort when wearing a pair of glasses is an essential design concern. This study examined the impact of aberrations on contact lenses to optimize a contact lens design for myopic and astigmatic eyes. In general, two aspherical surfaces can be assembled in an optical system to reduce the overall volume size. However, this design reduces the spherical aberration (SA) values at wide contact radii. The proposed optimization algorithm with optical design can be corrected to improve the SA value and, thus, reduce coma aberration (TCO) values and enhance the modulation transfer function (MTF). This means integrating a modified genetic algorithm (GA) with a neural network (NN) to optimize multiple-quality characteristics, namely the SA, TCO, and MTF, of contact lenses. When the proposed optional weight NN-GA is implemented, the weight values of the fitness function can be varied to adjust system performance. The method simplifies the selection of parameters in the optimization of optical systems. Compared with the traditional CODE V built-in optimal scheme, the proposed scheme is more flexible and intuitive to improve SA, TCO, and MTF values by 50.03%, 45.78%, and 24.7%, respectively.