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A Hybrid GA-SQP Algorithm for Analog Circuits Sizing
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作者 Firas Yengui Lioua Labrak +3 位作者 felipe frantz Renaud Daviot Nacer Abouchi Ian O’Connor 《Circuits and Systems》 2012年第2期146-152,共7页
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 ... 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. 展开更多
关键词 Genetic Algorithm Sequential QUADRATIC PROGRAMMING Hybrid Optimization ANALOG Circuits TRANSIMPEDANCE AMPLIFIER Optical Driver
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