Enhanced genetic algorithm kernel applied to a circuit-level optimization E-design environment

This paper presents a circuit/system-level optimization E-Design environment based on an enhanced modified genetic algorithm kernel. The presented approach improves the standard genetic algorithm implementation by including automatic search space decomposition, premature convergence prevention procedures and distributed processing features. In order to cover a broad range of solutions in terms of circuit/system complexity within a realistic execution time both behavioral simulation, using equation-based descriptions, and electrical simulation, using Spice-like simulators, are considered. Moreover, an E-Design front-end allowing an incremental growth of the IC design database, an individual management of each project and the widespread training on the design flow procedures is being developed. Finally, the achieved increase on optimization efficiency, compared to a standard genetic algorithm implementation, as well as the general purpose of the described approach are illustrated by a multiobjective, multi-constraint optimization of some well known circuits.