A model-based hybrid evolutionary algorithm for fast yield-inclusive design space exploration of analog circuits

This paper presents a multi-objective evolutionary algorithm based approach to yield-inclusive design space exploration of analog circuits. The yield objective function is included from the beginning in the optimization cycle, and is estimated economically by support vector regression models built from training data provided by the optimization process itself. We propose techniques to effectively handle the inaccurate nature of model-based yield estimates through various stages of the optimization process, and a two-level hybrid algorithm to keep the modeling cost reasonable. The experimental results presented for two real-world circuit examples look encouraging and show the effectiveness of the proposed method in providing designers with multiple trade-off choices