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This study presents a hybrid algorithm obtained by combining a genetic algorithm GA with successive quadratic sequential programming SQP, namely GA-SQP. GA is the main optimizer, whereas SQP is used to refine the results of GA, further improving the solution quality. The problem formulation is done in the framework named RUNE fRamework for aUtomated aNalog dEsign, which targets solving nonlinear mono-objective and multi-objective optimization problems for analog circuits design. Two circuits are presented: a transimpedance amplifier TIA and an optical driver Driver, which are both part of an Optical Network-on-Chip ONoC. Furthermore, convergence characteristics and robustness of the proposed method have been explored through comparison with results obtained with SQP algorithm. The outcome is very encouraging and suggests that the hybrid proposed method is very efficient in solving analog design problems.


Genetic Algorithm; Sequential Quadratic Programming; Hybrid Optimization; Analog Circuits; Transimpedance Amplifier; Optical Driver

Cite this paper

F. Yengui, L. Labrak, F. Frantz, R. Daviot, N. Abouchi and I. O’Connor -A Hybrid GA-SQP Algorithm for Analog Circuits Sizing,- Circuits and Systems, Vol. 3 No. 2, 2012, pp. 146-152. doi: 10.4236-cs.2012.32019.

Author: Firas Yengui, Lioua Labrak, Felipe Frantz, Renaud Daviot, Nacer Abouchi, Ian O’Connor

Source: http://www.scirp.org/


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