Elite genetic algorithms with adaptive mutations for solving continuous optimization problems - Application to modeling of the optical constants of solids

Abstract

The elite genetic algorithm with adaptive mutations is proposed as a tool for solving continuous optimization problems. The new algorithm and the corresponding classical genetic algorithm were severely tested on three families of multiminima test functions for 20, 50 and 100 variables. All performed tests proved that the introduced adaptive mutations significantly improve the ability of the algorithm to find a global minimum. After verifying the superiority of the proposed algorithm over the classical one on the test functions, an elite genetic algorithm with adaptive mutations was applied for solving the model parameter determination problem for modeling optical constants of the following metals: beryllium, chromium, nickel and palladium. Good agreement between calculated and experimental data was obtained for all four metals. © 1998 Elsevier Science B.V. All rights reserved.