Evolutionary Exploration of Triply Periodic Minimal Surfaces via Quality Diversity

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{bishop:2024:GECCO,

• author = "Jordan T Bishop and Jason Jooste and David Howard",
• title = "Evolutionary Exploration of Triply Periodic Minimal Surfaces via Quality Diversity",
• booktitle = "Proceedings of the 2024 Genetic and Evolutionary Computation Conference",
• year = "2024",
• editor = "Ruhul Sarker and Patrick Siarry and Julia Handl and Xiaodong Li and Markus Wagner and Mario Garza-Fabre and Kate Smith-Miles and Richard Allmendinger and Ying Bi and Grant Dick and Amir H Gandomi and Marcella Scoczynski Ribeiro Martins and Hirad Assimi and Nadarajen Veerapen and Yuan Sun and Mario Andres Munyoz and Ahmed Kheiri and Nguyen Su and Dhananjay Thiruvady and Andy Song and Frank Neumann and Carla Silva",
• pages = "1165--1173",
• address = "Melbourne, Australia",
• series = "GECCO '24",
• month = "14-18 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, triply periodic minimal surface, quality diversity, evolutionary design, constrained optimisation, Real World Applications",
• isbn13 = "979-8-4007-0494-9",
• DOI = "doi:10.1145/3638529.3654039",
• size = "9 pages",
• abstract = "Triply Periodic Minimal Surfaces (TPMSs) are a family of mathematical structures that exhibit constant zero mean curvature and 3-dimensional periodicity. They are often used to produce cellular solids with advantageous structural, thermal, and optical properties. Existing applications represent TPMSs as trigonometric approximations of a Fourier series. Due to the mathematical difficulty of determining new exact forms and their approximations, previous work has mostly evaluated metrics based on geometry, manufacturability, and mechanical performance across parameterisations of a small set of known TPMS equations. In this work, we define TPMS-like structures as having low estimated mean curvature, and apply a coupling of Grammatical Evolution and Quality Diversity to generate a diverse set of novel structures of this kind. We additionally explore the effect of being TPMS-like on the manufacturability of evolved structures. Results show that many TPMS-like designs can be found for different combinations of total surface area and Gaussian curvature, and that there is not a strong relationship between how TPMS-like a design is and its manufacturability. Our method serves as a basis for future application of novel TPMS-like structures and exploration of the pairing of evolutionary design with generative approaches from broader machine learning.",
• notes = "GECCO-2024 RWA A Recombination of the 33rd International Conference on Genetic Algorithms (ICGA) and the 29th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Jordan T Bishop Jason Jooste David Howard

Citations