Abstract
To improve evolutionary design of circuits in efficiency, scalability and optimizing capability, a genetic algorithm based approach was proposed. It employs a gate-level encoding scheme supporting flexible changes of functions and interconnections of comprised logic cells, a multi-objective evaluation mechanism of fitness with weight-vector adaptation and circuit simulation, and an adaptation strategy for crossover probability and mutation probability to vary with individuals’ diversity and genetic-search process. It was validated by experiments on arithmetic circuits, obtaining circuits with expected functions, novel structures, and higher performances in gate usage and operating speed as compared with the results of both conventional and evolutionary approaches. Moreover, by studying the circuits evolved for problems of increasing scales, some novel, efficient and generalized principles have been discerned, which are easy to verify but difficult to dig out by human experts with existing knowledge.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yao, X., Higuichi, T.: Promises and Challenges of Evolvable Hardware. IEEE Transactions on Systems Man and Cybernetics-Part C 29(1), 87–97 (1999)
Zhao, S.G.: Study of the Evolutionary Design Methods of Electronic Circuits. PhD. dissertation, Xidian University, China (2003)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Zhao, S.G., Yang, W.H.: Intrinsic Hardware Evolution Based on a Prototype of Function Level FPGA. Chinese Journal of Computers 25(6), 666–669 (2002)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Vassilev, V.K., Job, D., Miller, J.F.: Towards the Automatic Designof More Efficient Digital Circuits. In: Proceedings of the Second NASA/DOD Workshop on Evolvable Hardware (EH 2000), PaloAlto, pp. 151–160 (2000)
Coello Coello, A.C., Christiansen, A.D., Aguirre, A.H.: Use of Evolutionary Techniques to Automate the Design of Combinational Circuits. International Journal of Smart Engineering System Design 2(4), 299–314 (2000)
Miller, J.F., Job, D., Vassilev, V.K.: Principles in the Evolutionary Design of Digital Circuits: Part I. J. of Genetic Programming and Evolvable Machines 1(1), 8–35 (2000)
Shang, Y.C., Cai, X.M.: General Bionomics. Peiking University Press, Peiking (1992)
Gilbert, S.F.: Developmental Biology, 6th edn. Sinauer Assoc. Inc., Sunderland (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhao, S., Jiao, L., Zhao, J. (2005). Multi-objective Evolutionary Design and Knowledge Discovery of Logic Circuits with an Improved Genetic Algorithm. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_39
Download citation
DOI: https://doi.org/10.1007/11596448_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30818-8
Online ISBN: 978-3-540-31599-5
eBook Packages: Computer ScienceComputer Science (R0)