Theory of Evolutionary Systems Engineering

Simon John Hickinbotham, Rahul Dubey, Edgar Buchanan Berumen, Imelda Friel, Andrew Colligan, Mark Price, Andy Tyrrell

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Evolutionary approaches to engineering design in-
volve generating populations of candidate solutions that compete
via a selection process iteratively, to improve measures of perfor-
mance over many generations. The process of engineering design
is resistant to direct evolutionary approaches because the space of
possible designs is extremely large, with non-linear relationships
between the specification of the engineered artefact and its
performance criteria. Generative approaches use an indirect
encoding of the artefact, describing and exploiting iterative
growth processes in order to achieve the final form, but the
manufacturing process tends to be at most a minor consideration,
going against many of the principles of systems engineering.
Thus, 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.
Original languageEnglish
Title of host publication2023 IEEE Symposium Series on Computational Intelligence (SSCI)
Number of pages6
Publication statusAccepted/In press - 2023
2023 IEEE Symposium Series on Computational Intelligence: International Conference on Evolvable Systems (ICES)
- Mexico City, Mexico City, Mexico
Duration: 5 Dec 20238 Dec 2023


2023 IEEE Symposium Series on Computational Intelligence
Abbreviated titleSSCI
CityMexico City
Internet address

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