Optimization Algorithm of Evolutionary Design of Circuits Based on Genetic Algorithm

摘要：

For the convergence speed and scale bottlenecks of evolutionary design of circuits, the paper explores a new evolutionary method on the basis of genetic algorithm. Several optimization methods including fitness sharing, exponential weighting, double selection population, Queen bee mating, module crossover and optimal solution set are proposed to improve genetic algorithm. The new algorithm improved fitness evaluation method and genetic strategies. The experiment shows that the new evolutionary algorithm accelerates evolution convergence greatly, improves the adaptability effectively and expands the scale of evolved circuit obviously.

关键词： Evolutionary Design of Circuits Fitness Evaluation Genetic Algorithm Optimization Methods

作者: Xuejun Song Yanli Cui Aiting Li

作者单位: College of Physical Science and Information Engineering Hebei Normal University ShiJiaZhuang, China

会议类型: 国际会议

会议名称: 2012 Fifth International Symposium on Computational Intelligence and Design 第五届计算智能与设计国际会议 ISCID 2012

会议地点: 杭州

会议语种:英文

页码: 336-339

在线出版日期: 2012-10-28（万方平台首次上网日期，不代表论文的发表时间）