Find the 'Best' Solution from Multiple Analog Topologies via Pareto-Optimality

摘要

This paper presents a novel method using multi-objective optimization algorithm to automatically find the best solution from a topology library of analog circuits. Firstly this method abstracts the Pareto-front of each topology in the library by SPICE simulation. Then, the Pareto-front of the topology library is abstracted from the individual Pareto-fronts of topologies in the library followed by the theorem we proved. The best solution which is defined as the nearest point to specification on the Pareto-front of the topology library is then calculated by the equations derived from collinearity theorem. After the local searching using Nelder-Mead method maps the calculated best solution backs to design variable space, the non-dominated best solution is obtained. Comparing to the traditional optimization methods using single-objective optimization algorithms, this work can efficiently find the best non-dominated solution from multiple topologies for different specifications without additional time-consuming optimizing iterations. The experiments demonstrate that this method is feasible and practical in actual analog designs especially for uncertain or variant multi-dimensional specifications.