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JUCS
2006

Multi-Objective Evolutionary Algorithms and Pattern Search Methods for Circuit Design Problems

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Multi-Objective Evolutionary Algorithms and Pattern Search Methods for Circuit Design Problems
: 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. Key Words: Evolutionary electronics, multi-objective optimization, circuit design problems, evolutionary algorithms, genetic algorithms, classical optimization methods, pattern search methods, operational transconductance amplifier, leapfrog filter. Category: I.2.8, J.2, B.7.1, B.7.2
Tonio Biondi, Angelo Ciccazzo, Vincenzo Cutello, S
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where JUCS
Authors Tonio Biondi, Angelo Ciccazzo, Vincenzo Cutello, Santo D'Antona, Giuseppe Nicosia, Salvatore Spinella
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