AIDA-CMK: Multi-Algorithm Optimization Kernel applied to Analog IC Sizing

This work addresses the research and development (R&D) of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this work focus is AIDA-CMK, by enhancing AIDA-C with a new multi-objective multi-constraint optimization kernel. AIDA-C is the circuit optimizer component of AIDA, an electronic design automation framework fully developed in-house. The proposed solution implements three approaches to multi-objective multiconstraint optimization, namely, an evolutionary approach with NSGAII, a swarm intelligence approach with MOPSO and stochastic hill climbing approach with MOSA. Moreover, the implemented kernels allow an easy hybridization between them transforming a simple NSGAII optimization kernel to a more evolved and versatile multi algorithm and hybrid kernel. The three multi-objective optimization approaches were validated with CEC2009 benchmarks to constrained multiobjective optimization and tested with real analog IC design problems. The achieved results were compared in terms of performance, using statistical results obtained from multiple independent runs, finally, some hybrid approaches were also experimented, giving a foretaste to a wide range of opportunities to explore in future work.