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

被引:16
作者
Zhao S. [1 ]
Jiao L. [2 ]
机构
[1] College of Information Sciences and Technology, Donghua University
[2] School of Electronic Engineering, Xidian University
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Adaptive genetic algorithm; Evolutionary design of circuits; Evolvable hardware; Knowledge discovery; Multi-objective genetic algorithm;
D O I
10.1007/s10710-006-9005-7
中图分类号
学科分类号
摘要
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. © Springer Science+Business Media, LLC 2006.
引用
收藏
页码:195 / 210
页数:15
相关论文
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