Optimal design of second generation current conveyors by the Artificial Bee Colony technique

The field of metaheuristics based on swarm intelligence (SI) techniques, for the application to analog design optimization is a rapidly growing domain of research. This is due to the importance of these metaheuristics to solve NP-hard problem. The main goal of this paper is to use the Artificial Bees Colony (ABC) technique to the optimal sizing of analog circuits. The paper details the proposed algorithm and highlights its performances using some mathematical test functions. An application to the optimal sizing of CMOS second generation current conveyors (CCII) for specific performances is presented, and comparison results with published works are highlighted. SPICE simulation results are given to show the viability of the suggested algorithm.

[1]  M. Loulou,et al.  Comparison between PSO and ACO techniques for analog circuit performance optimization , 2011, ICM 2011 Proceeding.

[2]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[3]  Randy L. Haupt,et al.  Practical Genetic Algorithms , 1998 .

[4]  Yves Crama,et al.  Local Search in Combinatorial Optimization , 2018, Artificial Neural Networks.

[5]  Dervis Karaboga,et al.  A comprehensive survey: artificial bee colony (ABC) algorithm and applications , 2012, Artificial Intelligence Review.

[6]  B. Benhala,et al.  Multi-objective optimization of second generation current conveyors by the ACO technique , 2012, 2012 International Conference on Multimedia Computing and Systems.

[7]  Mourad Loulou,et al.  Analog circuit design optimization through the particle swarm optimization technique , 2010 .

[8]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[9]  Johann Dréo,et al.  Metaheuristics for Hard Optimization: Methods and Case Studies , 2005 .

[10]  Mourad Loulou,et al.  Application of swarm intelligence techniques to the design of analog circuits: evaluation and comparison , 2013 .

[11]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

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

[13]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[14]  Manoj Kumar Tiwari,et al.  Swarm Intelligence, Focus on Ant and Particle Swarm Optimization , 2007 .

[15]  A. Rodríguez-Vázquez,et al.  Global design of analog cells using statistical optimization techniques , 1994 .

[16]  J. B. Grimbleby,et al.  Automatic analogue circuit synthesis using genetic algorithms , 2000 .

[17]  Bachir Benhala,et al.  Sizing of current conveyors by means of an Ant Colony Optimization technique , 2011, 2011 International Conference on Multimedia Computing and Systems.

[18]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[19]  J. K. Lenstra,et al.  Local Search in Combinatorial Optimisation. , 1997 .

[20]  Guy Theraulaz,et al.  The biological principles of swarm intelligence , 2007, Swarm Intelligence.