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A Hybrid GA-SQP Algorithm for Analog Circuits Sizing

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DOI: 10.4236/cs.2012.32019    4,279 Downloads   6,961 Views   Citations

ABSTRACT

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.

Conflicts of Interest

The authors declare no conflicts of interest.

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.

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