\chapter*{Abstract}

On the crossroads between the fields of evolutionary computation, parallel systems and VLSI design, the Parallel Selfish Gene Algorithm (PSG) is situated. PSG is a new parallel evolutionary algorithm based on recent developments in modern evolutionary biology.

This thesis studies existing evolutionary and parallel evolutionary algorithms, outlining the state of the art in the field, and describes the design and implementation of PSG. The algorithm is subjected to a comprehensive set of experiments evaluating its performance in solving the difficult problem of evolving high quality test pattern generators for the built-in self-test of digital circuits.

The outcome is favorable; PSG is a processor-efficient algorithm. The extension onto multiple processors gives users the ability to reduce execution time or increase solution quality. Furthermore, the test pattern generators evolved by the algorithm are of a high quality, achieving fault coverage rates not normally obtained by heuristic methods.

