Multiobjective Differential Evolution Algorithm using Crowding Distance for the Optimal Design of Analog Circuits

被引：0
|
作者：
El Dor, Abbas [1 ]
Fakhfakh, Mourad [2 ]
Siarry, Patrick [3 ]
机构：
[1] Ecole Mines Nantes, TASC, INRIA, CNRS,UMR 6241, 4 Rue Alfred Kastler, F-44300 Nantes, France
[2] Univ Sfax, ENET Com, BP 1163, Sfax 3018, Tunisia
[3] Univ Paris Est Creteil, LiSSi, EA 3956, 122 Rue Paul Armangot, F-94400 Vitry Sur Seine, France
来源：
JOURNAL OF ELECTRICAL SYSTEMS | 2016年 / 12卷 / 03期
关键词：
Metaheuristics; Multiobjective optimization; MODE; NSGA-II; CMOS; Second generation current conveyor;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper details the Multiobjective Differential Evolution algorithm (MODE) using crowding distance for the sizing of analog circuits. MODE is used to compute the Pareto front of a bi-objective optimization problem, namely maximizing the high current cut-off frequency and minimizing the parasitic input resistance of a second generation current conveyor. To highlight performances of MODE, comparisons with the non-sorting genetic algorithm (NSGA-II) were performed. These comparisons show that MODE outperforms NSGA-II in terms of quality of the optimal solutions, diversity of those solutions along the Pareto front, and computing time.
引用
收藏
页码：612 / 622
页数：11
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