基于改进型遗传算法的数字电路优化

遗传算法（ Genetic Algorithm,GA）是一种模拟生物界自然选择的智能优化算法,已经被广泛应用到各个领域。文中主要针对传统遗传算法在应用于数字电路优化设计中时所出现的未成熟收敛和收敛速度慢的问题,提出一种新的个体选择方法。该方法将保留最优个体选择方式和改进轮盘赌选择方式相结合,能够在保持种群的多样性的同时有效地提高数字电路优化的精确度。将该算法应用到最小分类网络的设计中,实验结果验证了改进算法的合理性和有效性。

Optimization of Digital Circuits Based on Improved Genetic Algorithm

Genetic Algorithm （ GA） is an intelligent optimization algorithm by simulation of biological evolution,which has been widely used in lots of fields. In view of the problems of precocity and slow evolution speed in the digital circuits design where traditional GA applies,propose a new individual selection method. By combining the optimal individual and improving roulette,it is able to keep the diversity of population and effectively improve the accuracy of circuit optimization at the mean time. The algorithm is applied in minimum classification network design,the experimental results verify its rationality and effectiveness.