Comparison of the classical dumped least squares and genetic algorithm in the optimization of the doublet
Darko M. Vasiljevic, Janez Golobič · 2007
The Comparison of the classical dumped least squares and genetic algorithm in the optimization of the doublet is given. Both optimization methods are described with review of the advantages and the shortcomings for each method. Simulation results of executions of both methods are discussed. It is shown that genetic algorithm optimization finds better doublet i.e. with smaller merit function than classical dumped least squares method. 1. Introduction Problem of the automatic lens design and optimization of the optical systems is very old. Many researchers proposed various methods or their improvement in order to solve this problem, which belongs to a class of highly nonlinear optimization problem. All those methods can be classified in two broad groups: . classical optimization methods which include least squares (LS), steepest descent (SD), damped least squares (DLS), pseudo second derivation (PSD). . modern optimization methods which are based on analogies found in nature like simu...