Differential Evolution Algorithm using Crowding Distance for the Optimal Design of Analog Circuits

This paper details the Multiobjective Differential Evolution algorithm (MODE) using crowding distance for the sizing of analog circuits. MODE is used to compute the Pareto front of a biobjective optimization problem, namely maximizing the high current cut-off frequency and minimizing the parasitic input resistance of a second generation current conveyor. To highlight performances of MODE, comparisons with the non-sorting genetic algorithm (NSGA-II) were performed. These comparisons show that MODE outperforms NSGA-II in terms of quality of the optimal solutions, diversity of those solutions along the Pareto front, and computing time.

[1]  Maurice Clerc,et al.  Hybridization of Differential Evolution and Particle Swarm Optimization in a New Algorithm: DEPSO-2S , 2012, ICAISC.

[2]  Rafael Castro-Lopez,et al.  Analog/RF and Mixed-Signal Circuit Systematic Design , 2013 .

[3]  Esteban Tlelo-Cuautle.  Integrated Circuits for Analog Signal Processing , 2014 .

[4]  Samir Ben Salem,et al.  A high performances CMOS CCII and high frequency applications , 2006 .

[5]  Brett Wilson,et al.  Current mode signal processing circuits , 1988, 1988., IEEE International Symposium on Circuits and Systems.

[6]  I. A. Awad,et al.  Inverting second generation current conveyors: the missing building blocks, CMOS realizations and applications , 1999 .

[7]  Mourad Fakhfakh,et al.  Performance optimization of CMOS second generation current conveyors using a multi-swarm algorithm , 2014 .

[8]  Mourad Loulou,et al.  Live demonstration: CASCADES. 1: A flow-graph-based symbolic analyzer , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[9]  Mourad Fakhfakh,et al.  Design of second-generation current conveyors employing bacterial foraging optimization , 2010, Microelectron. J..

[10]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[11]  K. Smith,et al.  A second-generation current conveyor and its applications , 1970, IEEE Transactions on Circuit Theory.

[12]  Andrew R. Conn,et al.  Optimization of custom MOS circuits by transistor sizing , 1996, ICCAD 1996.

[13]  Millie Pant,et al.  An efficient Differential Evolution based algorithm for solving multi-objective optimization problems , 2011, Eur. J. Oper. Res..

[14]  Prospero C. Naval,et al.  An effective use of crowding distance in multiobjective particle swarm optimization , 2005, GECCO '05.

[15]  Arthur C. Sanderson,et al.  Pareto-based multi-objective differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..