Investigation of starting conditions in generative processes for the design of engineering structures

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

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


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.
Original languageEnglish
Title of host publication2023 IEEE Symposium Series on Computational Intelligence
Subtitle of host publicationInternational Conference on Evolvable Systems (ICES)
Publication statusAccepted/In press - 15 Sept 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


  • evodevo
  • generative design
  • structural engineering
  • genetic algorithm
  • Neural network

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