Analog cell sizing using enhanced multi-objective evolutionary algorithm (MOEA/D-DE) and forming a feedback loop interface between SACSES and TOLAS

Abstract

This thesis investigates an evolutionary-based design system for automated sizing of analog integrated circuits (ICs). A new algorithm, called multi-objective evolutionary algorithm based on decomposition using enhanced differential evolution (MOEAD/DDE), is proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through electrical simulation, to the optimization system in the MATLAB environment, once a circuit topology is selected. The method has been tested through the sizing of several analog circuits and benchmark problems. The results show that design specifications are met and objective functions are highly optimized. Comparisons with available methods like NSGA-II, are also carried out, showing that the proposed algorithm has important advantages in terms of diversity and optimization quality. As a final work, an interface environment is created to link another optimization system (SACSES) to layout generator. This feedback loop lets the optimization to take into account the parasitic effects after the layout is drawn by TOLAS.|Keywords : Evolutionary algorithms, multiobjective optimization problems, pareto optimality.