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Multi-objective evolutionary design and knowledge discovery of logic circuits based on an adaptive genetic algorithm

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Abstract

Evolutionary design of circuits (EDC), an important branch of evolvable hardware which emphasizes circuit design, is a promising way to realize automated design of electronic circuits. In order to improve evolutionary design of logic circuits in efficiency, scalability and capability of optimization, a genetic algorithm based novel approach was developed. It employs a gate-level encoding scheme that allows flexible changes of functions and interconnections of logic cells comprised, and it adopts a multi-objective evaluation mechanism of fitness with weight-vector adaptation and circuit simulation. Besides, it features an adaptation strategy that enables crossover probability and mutation probability to vary with individuals' diversity and genetic-search process. It was validated by the experiments on arithmetic circuits especially digital multipliers, from which a few functionally correct circuits with novel structures, less gate count and higher operating speed were obtained. Some of the evolved circuits are the most efficient or largest ones (in terms of gate count or problem scale) as far as we know. Moreover, some novel and general principles have been discerned from the EDC results, which are easy to verify but difficult to dig out by human experts with existing knowledge. These results argue that the approach is promising and worthy of further research.

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Acknowledgments

This project was partially supported by National Natural Science Foundation of China under grants No. 60133010 and No. 60374063. It was also granted financial support from China Postdoctoral Science Foundation.

The authors would like to thank the editors and the anonymous reviewers for their helpful comments and suggestions. They would also thank Mr. Wenhe Feng and Ms. Wei Lee for their generous help in improving English writing of this paper

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Authors and Affiliations

  1. College of Information Sciences and Technology, Donghua University, Shanghai, 201620, P. R. China

    Shuguang Zhao

  2. School of Electronic Engineering, Xidian University, Xi'an, 710071, P. R. China

    Licheng Jiao

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  1. Shuguang Zhao
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  2. Licheng Jiao
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Correspondence to Shuguang Zhao.

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Zhao, S., Jiao, L. Multi-objective evolutionary design and knowledge discovery of logic circuits based on an adaptive genetic algorithm. Genet Program Evolvable Mach 7, 195–210 (2006). https://doi.org/10.1007/s10710-006-9005-7

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  • DOI: https://doi.org/10.1007/s10710-006-9005-7

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