Evolving Design Modifiers

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

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


Evolutionary Developmental biology (EvoDevo) is a process of directed growth whose mechanisms could be used in an evolutionary algorithm for engineering applications. Engineering design can be thought of as a search through a high-dimensional design space for a small number of solutions that are optimal by various metrics. Configuring this search within an EvoDevo algorithm may allow developmental processes to provide a facility to give more immediate, localised feedback to the system as it grows into its final optimal configuration (form). This approach would augment current design practices. The main components needed to run EvoDevo for engineering design are set out in this paper, and these are developed into an algorithm for initial investigations, resulting in evolved neural network-based structural design modifying operators that optimise the structure of a planar truss in an iterative, decentralized manner against multiple objectives. Preliminary results are presented which show that the two levels feedback at the Evo and Devo stages drive the system to ultimately produce feasible solutions.
Original languageEnglish
Title of host publication2022 IEEE Symposium Series on Computational Intelligence (SSCI)
Publication statusPublished - 7 Dec 2022

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