Evolving Design for Engineering Structures
Abstract
In recent years, the evolutionary developmental (Evo- Devo) concept has gained traction in the field of engineering design. This paper presents a new biologically inspired approach rooted in Evo- Devo principles to iteratively develop car chassis designs based on a specified design brief. The proposed method draws inspiration from biological cell growth and differentiation behaviors to generate intricate engineering designs. Employing evolutionary algorithms, the paper aims to evolve gene regulatory networks that govern the growth of a minimal viable design. The primary goal is to achieve an optimal design capable of withstanding sudden crash impacts within safety limits. Comprehensive simulation results demonstrate that the proposed approach, using genetic algorithms, evolves gene regulatory networks that generate a spectrum of viable designs. Furthermore, the best-evolved solution exhibits generalizability and adaptability across different simulation parameters.
Department(s)
Computer Science
Document Type
Conference Proceeding
DOI
10.1109/CEC60901.2024.10611851
Keywords
engineering design, genetic algorithms, GRN, neural networks
Publication Date
1-1-2024
Recommended Citation
Dubey, Rahul; Hickinbotham, Simon; Buchanan, Edgar; Colligan, Andrew; Briel, Imelda; Price, Mark; and Tyrrell, Andy M., "Evolving Design for Engineering Structures" (2024). Faculty Scholarship. 493.
https://bearworks.missouristate.edu/articles00/493
Journal Title
2024 IEEE Congress on Evolutionary Computation CEC 2024 Proceedings
