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

Katsumi HOMMA
Toshiyuki SHIBUYA

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E92-A    No.12    pp.3035-3043
Publication Date: 2009/12/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E92.A.3035
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
Category: Device and Circuit Modeling and Analysis
analog design,  topology selection and sizing,  automation,  multi-objective optimization,  Pareto-optimality,  

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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.