JUCS - Journal of Universal Computer Science 12(4): 432-449, doi: 10.3217/jucs-012-04-0432
Multi-Objective Evolutionary Algorithms and Pattern Search Methods for Circuit Design Problems
Tonio Biondi‡, Angelo Ciccazzo‡, Vincenzo Cutello§, Santo D Antona§, Giuseppe Nicosia§, Salvatore Spinella|‡ STMicroeletronics, Italy§ University of Catania, Italy| University of Calabria, Italy
Corresponding author: Tonio Biondi ( tonio.biondi@st.com ) © Tonio Biondi, Angelo Ciccazzo, Vincenzo Cutello, Santo Antona, Giuseppe Nicosia, Salvatore Spinella. This article is freely available under the J.UCS Open Content License. Citation:
Biondi T, Ciccazzo A, Cutello V, Antona SD, Nicosia G, Spinella S (2006) Multi-Objective Evolutionary Algorithms and Pattern Search Methods for Circuit Design Problems. JUCS - Journal of Universal Computer Science 12(4): 432-449. https://doi.org/10.3217/jucs-012-04-0432 |  |
Abstract
The paper concerns the design of evolutionary algorithms and pattern search methods on two circuit design problems: the multi-objective optimization of an Operational Transconductance Amplifier and of a fifth-order leapfrog filter. The experimental results obtained show that evolutionary algorithms are more robust and effective in terms of the quality of the solutions and computational effort than classical methods. In particular, the observed Pareto fronts determined by evolutionary algorithms has a better spread of solutions with a larger number of nondominated solutions when compared to the classical multi-objective techniques.
Keywords
evolutionary electronics, multi-objective optimization, circuit design problems, evolutionary algorithms, genetic algorithms, classical optimization methods, pattern search methods, operational transconductance amplifier, leapfrog filter