Automated Shape Design by Grammatical Evolution

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10198)

Abstract

This paper proposes a automated shape generation methodology based on grammatical genetic programming for specific design cases. Two cases of the shape generation are presented: architectural envelope design and facade design. Through the described experiments, the applicability of this evolutionary method for design applications is showcased. Through this study it can be seen that automated shape generation by grammatical evolution offers a huge potential for the development of performance-based creative systems.

Keywords

Shape generation Design Genetic programming 

References

  1. 1.
    Byrne, J.: Approaches to evolutionary architectural design exploration using grammatical evolution. University College Dublin (2012)Google Scholar
  2. 2.
    Ceccato, C.; Simondetti, A.; Burry, M.C.: Mass-customization in design using evolutionary and parametric methods. In: Proceedings of the 2000 ACADIA Conference (2000)Google Scholar
  3. 3.
    Duarte, J.P.: Towards the mass customization of housing: the grammar of Siza’s houses at Malagueira. Environ. Plan. B: Plan. Des. 32(3), 347–380 (2005)CrossRefGoogle Scholar
  4. 4.
    Frazer, J.: An Evolutionary Architecture. Architectural Association, London (1995)Google Scholar
  5. 5.
    Heisserman, J.; Woodbury, R.: Generating languages of solid models. In: SMA 1993 Proceedings on the Second ACM Symposium on Solid Modeling and Applications, pp. 103–112 (1993)Google Scholar
  6. 6.
    Janssen, P.; Kaushik, V.: Evolving lego. Exploring the impact of alternative encodings on the performance of evolutionary algorithms. In: Rethinking Comprehensive Design: Speculative Counterculture, Proceedings of the 19th International Conference on Computer-Aided Architectural Design Research in Asia CAADRIA 2014, pp. 523–532 (2014)Google Scholar
  7. 7.
    Janssen, P.: A design method and computational architecture for generating and evolving building designs. The Hong Kong Polytechnic University (2004)Google Scholar
  8. 8.
    Koning, H., Eizenberg, J.: The language of the prairie. Frank Lloyd Wright’s prairie houses. Environ. Plan. B: Plan. Des. 8(3), 295–323 (1981)CrossRefGoogle Scholar
  9. 9.
    Koza, J.R.: Genetic programming. a paradigm for genetically breeding populations of computer programs to solve problems. Stanford University (1990)Google Scholar
  10. 10.
    Langdon, W.B.: Genetic Programming and Data Structures. Genetic Programming + Data Structures = Automatic Programming!. Genetic Programming. Springer, Boston (1998). doi:10.1007/978-1-4615-5731-9 CrossRefMATHGoogle Scholar
  11. 11.
    Lee, H.C., Herawan, T., Noraziah, A.: Evolutionary grammars based design framework for product innovation. Procedia Technol. 1, 132–136 (2012). doi:10.1016/j.protcy.2012.02.026 CrossRefGoogle Scholar
  12. 12.
    McDermott, J.: Graph grammars for evolutionary 3D design. Genet. Program Evolvable Mach. 14(3), 369–393 (2013). doi:10.1007/s1071001391900 CrossRefGoogle Scholar
  13. 13.
    Montana, D.J.: Strongly typed genetic programming. Evol. Comput. 3(2), 199–230 (1995). doi:10.1162/evco.1995.3.2.199 CrossRefGoogle Scholar
  14. 14.
    O’Neill, M., Ryan, C.: Grammatical evolution. IEEE Trans. Evol. Comput. 5(4), 349–358 (2001). doi:10.1109/4235.942529 CrossRefGoogle Scholar
  15. 15.
    Poli, R., Langdon, W.B., McPhee, N.F., Koza, J.R.: A Field Guide to Genetic Programming. Lulu Press, Raleigh (2008). lulu.com
  16. 16.
    Roudavski, A.: Towards morphogenesis in architecture. Int. J. Architect. Comput. 7(3), 345–374 (2009). doi:10.1260/147807709789621266 CrossRefGoogle Scholar
  17. 17.
    Ryan, C., Collins, J.J., Neill, M.O.: Grammatical evolution: evolving programs for an arbitrary language. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds.) EuroGP 1998. LNCS, vol. 1391, pp. 83–96. Springer, Heidelberg (1998). doi:10.1007/BFb0055930 CrossRefGoogle Scholar
  18. 18.
    Stiny, G., Mitchell, W.J.: The palladian grammar. Environ. Plan. B: Plan. Des. 5(1), 5–18 (1978)CrossRefGoogle Scholar
  19. 19.
    Williams, N., et al.: FabPod: designing with temporal flexibility & relationships to mass-customisation. Autom. Constr. 51, 124–131 (2015)CrossRefGoogle Scholar
  20. 20.
    Woodbury, R.F., Burrow, A.L.: Whither design space? Artif. Intell. Eng. Des. Anal. Manufact. 20, 63–82 (2006)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Spatial Information Architecture Laboratory (SIAL)RMIT University MelbourneCarltonAustralia
  2. 2.Evolutionary Computation and Machine Learning GroupRMIT University MelbourneCarltonAustralia

Personalised recommendations