Efficiently finding the 'best' solution with multi-objectives from multiple topologies in topology library of analog circuit

ABSTRACT

This paper presents a new 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 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 back to design variable space, the non-dominated best solution is obtained.

Comparing to the 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 different multidimensional specifications.

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