摘要
在应用微型化技术进行大规模模拟集成电路设计过程中,存在多个性能指标相互冲突的问题,因此,提出一种精英导向型多目标差分变异烟花算法(GMOFWA-DV),利用粒子进化信息引导爆炸,提高算法搜索效率,同时采用差分算法中变异、交叉综合变异方式,增强粒子间信息交流以及导向策略的适用性.将该方法与其他3种算法进行仿真实验比较,实验结果验证了所提出算法的有效性.将该方法应用于CMOS模拟集成电路设计参数优化的实际工程应用中,可以降低模拟集成电路设计的开发周期.
In the process of large-scale analog integrated circuit design using miniaturization technology,there are some problems of conflicting performance indicators.An elitist guided multi-objective fireworks algorithm with difference variation(GMOFWA-DV)is proposed in this paper.Particle evolution information is used to guide the explosion and improve the efficiency of the algorithm.In order to enhance the information exchange between particles and facilitate the application of the guidance strategy,the mutation and cross operators in the differential algorithm are adopted in variation of the GMOFWA-DV.Simulation experiments of the comparision of the designed algorithm with 3 others are conducted.The experimental results verify the effectiveness of the proposed algorithm.The application of the GMOFWA-DV in the practical engineering application of CMOS analog integrated circuit design parameter optimization can reduce the development cycle of analog integrated circuit design.
作者
陈思溢
胡拚
黄辉先
CHEN Si-yi;HU Pin;HUANG Hui-xian(College of Information Engineering,Xiangtan University,Xiangtan 411105,China)
出处
《控制与决策》
EI
CSCD
北大核心
2020年第1期55-64,共10页
Control and Decision
基金
国家部委预先研究基金项目(20170101)
湘潭大学校级科研项目(2017XZX22)
湘潭大学省级重点学科项目(11kz1kz05002).
关键词
CMOS模拟电路
优化设计
精英导向
差分
多目标
烟花算法
CMOS analog circuit
optimal design
elitist guided
difference
multi-objective
fireworks algorithm
作者简介
通讯作者;陈思溢,E-mail:c.siyi@xtu.edu.cn.
