Effective mutation rate for probabilistic models in evolutionary analog circuit design

This paper represents the following improvement of evolutionary analog circuit design on the base of the univariate marginal distribution algorithm. Experiments have indicated that the high mutation rate increases the success rate, although the computational expenses are increased as well. An effective mutation rate is considered with respect to a high success rate and small computational expenses. Experiments for analog arrays are discussed.

[1]  Lyudmila Zinchenko,et al.  Evolutionary design of electronic devices , 2000, ICECS 2000. 7th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.00EX445).

[2]  Domine Leenaerts,et al.  DARWIN: CMOS opamp Synthesis by Means of a Genetic Algorithm , 1995, 32nd Design Automation Conference.

[3]  Jason D. Lohn,et al.  A circuit representation technique for automated circuit design , 1999, IEEE Trans. Evol. Comput..

[4]  J. B. Grimbleby,et al.  Hybrid genetic algorithms for analogue network synthesis , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[5]  Heinz Mühlenbein,et al.  Optimal Mutation Rate Using Bayesian Priors for Estimation of Distribution Algorithms , 2001, SAGA.

[6]  Heinz Mühlenbein,et al.  The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.

[7]  Rob A. Rutenbar,et al.  Synthesis tools for mixed-signal ICs: progress on frontend and backend strategies , 1996, DAC '96.

[8]  Jong-Hwan Kim,et al.  Genetic quantum algorithm and its application to combinatorial optimization problem , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[9]  Marley M. B. R. Vellasco,et al.  Comparison of different evolutionary methodologies applied to electronic filter design , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[10]  P. Nordin.  Genetic Programming III - Darwinian Invention and Problem Solving , 1999 .

[11]  Yun Li,et al.  GA automated design and synthesis of analog circuits with practical constraints , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).