Theory of Evolutionary Systems Engineering.

Evolutionary approaches to engineering design involve generating populations of candidate solutions that compete via a selection process iteratively, to improve measures of performance over many generations. Although the attractive properties of biological evolutionary systems have motivated researchers to investigate emulating them for engineering design, there has been an emphasis on using encodings of the technical artefacts themselves, rather than encoding a complete bio-inspired system which is capable of producing such artefacts. It is the latter approach which is the subject of this contribution: how might a bio-inspired system be designed that self-organises the process of engineering design and manufacture? To make progress in the application of evolutionary processes to problems in engineering design, the evolutionary model must encompass the complexity of systems engineering. A new theory of evolutionary systems engineering is presented, based on von Neumann's Universal Constructor Architecture (UCA), drawing from more recent understanding of biology and applying the resulting system to the task of engineering design. It demonstrates how individual bioinspired algorithms fit into a coherent whole, and how they can be combined to drive open-endedness in automated design. The resulting system provides a common language for multidisciplinary applications in generative design, whereby industrial systems engineering approaches can be developed using principles from the UCA for the first time.