Algorithm for global optimization of optical systems based upon genetic competition

Global optimization of optical system designs is difficult because of the complex solution space and extreme non-linearity of system performance with respect to design parameters. Genetic algorithms (GA's) have been used to effectively solve complex non-linear optimization in other fields of science. GA's model each design parameter as part of a genetic code for an imaginary creature, and the system performance is interpreted to be the fitness for survival of this creature. The GA's goal is to improve the system performance by selective breeding of simulated creatures to yield simulated offspring with desirable traits. An algorithm for doing this along with results will be presented.