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 biobjective
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.
关键词：Metaheuristics; Multiobjective optimization; MODE; NSGA-II; CMOS; Second;
generation current conveyor.
