On the impact of modelling, robustness and diversity to the performance of a multi-objective evolutionary algorithm for digital VLSI system design

This paper describes the operation of an evolutionary algorithm (EA) for the creation of linear digital VLSI circuit designs. The EA can produce hardware designs from a behavioural description of a problem. The designs are based upon a library of high-level components. The EA performs a multi-objective search, using models of the longest-path delay and the silicon area of a design. These models are based upon the properties of real-world components, implementable in a 0.18 micron technology. The accuracy of these models is investigated. Two important aspects of multi-objective evolution are the population diversity, and the variability of the results. Both of these areas are examined. The population diversity is assessed in terms of conflict between the objectives, and the robustness of the EA is experimentally investigated.