Buchanan Berumen, Edgar orcid.org/0000-0001-6587-8808, Dubey, Rahul orcid.org/0000-0003-1524-7797, Hickinbotham, Simon John orcid.org/0000-0003-0880-4460 et al. (4 more authors) (Accepted: 2023) Investigation of starting conditions in generative processes for the design of engineering structures. In: 2023 IEEE Symposium Series on Computational Intelligence:International Conference on Evolvable Systems (ICES). 2023 IEEE Symposium Series on Computational Intelligence, 05-08 Dec 2023 , MEX (In Press)
Abstract
Engineering design has traditionally involved human engineers manually creating and iterating on designs based on their expertise and knowledge. Bio-inspired Evolutionary Development (EvoDevo) generative algorithms aim to explore a much larger design space that may not have ever been considered by human engineers. However, for complex systems, the designer is often required to start the EvoDevo process with an initial design solution (seed) which the development process will optimize. The question is will a relatively good starting seed always yield a good set of design solutions. This paper considers this question and suggests that sub-optimal seeds can provide, up to certain limits, better design solutions than relatively more optimal seeds. In addition, this paper highlights the importance of designing the appropriate seed for the appropriate problem. In this paper, the problem analysed is the structural performance of a Warren Truss (bridge-like structure) under a single load. The main conclusion of this paper is that up to a limit sub-optimal seeds provide in general better sets of solutions than more optimal seeds. After this limit, the performance of sub-optimal seed starts to degrade as parts of the phenotype landscape become inaccessible.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | evodevo,generative design,structural engineering,genetic algorithm,Neural network |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Funding Information: | Funder Grant number EPSRC EP/V007335/1 |
Depositing User: | Pure (York) |
Date Deposited: | 18 Sep 2023 14:00 |
Last Modified: | 21 Jan 2025 18:27 |
Status: | In Press |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203406 |