Skip to main content

An Evolutionary Framework for Enhancing Design

A kernel of computational systems for enhancing design with dynamic structure of hierarchical representations

  • Chapter
Artificial Intelligence in Design ’02

Abstract

A computational framework for enhancing design in an evolutionary approach with a dynamic hierarchical structure is presented in this paper. This framework can be used as an evolutionary kernel for building computer-supported design systems. It provides computational components for generating, adapting and exploring alternative design solutions at multiple levels of abstraction with hierarchically structured design representations. In this paper, preliminary experimental results of using this framework in several design applications are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Akin, O and Akin, C: 1996, Frames of reference in architectural design: analyzing the hyperacclamation (A-h-a!), Design Studies 17: 341–361.

    Article  Google Scholar 

  • Akin, O and Akin, C: 1998, On the process of creativity in puzzles, inventions and designs, Automation in Construction 7: 123–138.

    Article  Google Scholar 

  • Back, T: 1996, Evolutionary Algorithms in Theory and Practice, Oxford University Press, Oxford.

    Google Scholar 

  • Bentley, PI (ed.): 1999, Evolutionary Design by Computers, Morgan Kaufmann, San Francisco, CA.

    MATH  Google Scholar 

  • Campbell, M, Cagan, J and Kotovsky, K: 1998, A-Design: Theory and implementation of an adaptive agent-based method of conceptual design, in Gero, JS and Sudweeks, F (eds), Artificial Intelligence in Design ‘88, Kluwer, Dordrecht, pp. 579–598.

    Chapter  Google Scholar 

  • Chan, KH, Frazer, J and Tang, MX: 2000, Handling the evolution and hierarchy nature of designing in computer-based design support systems, Proceedings of the Third International Conference Computer-Aided Industrial Design and Conceptual Design (CAID & CD 2000), International Academic Publishers, Hong Kong, pp. 447–454.

    Google Scholar 

  • Cross, N: 1997, Descriptive models of creative design: application to an example, Design Studies 18: 427–455.

    Article  Google Scholar 

  • Das, R, Crutchfield, JP, Mitchell, M and Hanson, JE: 1995, Evolving globally synchronized cellular automata, in LJ Eshelman (ed.), Proceedings of the Sixth International Conference on Genetic Algorithms, Morgan Kaufmann, San Francisco, pp. 336–343.

    Google Scholar 

  • Eiben, AE: 1996, Evolutionary exploration of search spaces, in Z Ras and M Michalewicz (eds), Proceedings of Foundations of Intelligent Systems: 9th International Symposium, ISMIS ‘86, Springer, New York, pp. 178–188.

    Chapter  Google Scholar 

  • Fogel, DB: 1995, Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press, New York.

    Google Scholar 

  • Frazer, J: 1995, An Evolutionary Architecture, Architecture Association, London.

    Google Scholar 

  • Garza, AGDS and Maher, ML: 2000, A process model for evolutionary design case adaptation, in JS Gero (ed.), Artificial Intelligence in Design ‘00, Kluwer, Dordrecht, pp. 393–412.

    Google Scholar 

  • Gero, JS, Kazakov, VA and Schnier, T: 1997, Genetic engineering and design problems, in D Dasgupta and Z Michalewicz (eds), Evolutionary Algorithms in Engineering Applications, Springer, Berlin, pp. 47–69.

    Google Scholar 

  • Graf, J: 1995, Interactive evolutionary algorithms in design, International Conference on Artificial Neural Networks and Genetic Algorithms ICANNGA ‘85, Ecole des Mines d’AI `es, France, pp. 227–230.

    Book  Google Scholar 

  • Heisserman, J, Callahan, S and Mattikalli, R: 2000, A design representation to support automated design generation, in JS Gero (ed.), Artificial Intelligence in Design ‘00, Kluwer, Dordrecht, pp. 545–566.

    Google Scholar 

  • Hintersteiner, JD: 1999, A fractal representation for systems, in H Kals and FV Houten (eds), Integration of process knowledge into design support systems: Proceedings of the 1999 CIRP International Design Seminar, Kluwer, Boston, MA, pp. 427–436.

    Google Scholar 

  • Liu, Y, Chrabarti, A and Bligh, T: 2000, A computational framework for concept generation and exploration in mechanical design, in JS Gero (ed.), Artificial Intelligence in Design ‘00, Kluwer, Dordrecht, pp. 499–519.

    Google Scholar 

  • Michalewicz, Z, Xiao, J and Trojanowski, K: 1996, Evolutionary computation: one project, many directions, in Z Ras and M Michalewicz (eds), Proceedings of Foundations of Intelligent Systems: 9th International Symposium, ISMIS ‘86, Springer, New York, pp. 189–201.

    Chapter  Google Scholar 

  • Parmee, I, Cvetkovic, D and Bonham, C: 2000, Interactive evolutionary conceptual design systems, in JS Gero (ed.), Artificial Intelligence in Design’00, Kluwer, Dordrecht, pp. 249–268.

    Google Scholar 

  • Peak, RS, Fulton, RE, Nishigaki, I and Okamoto, N: 1998, Integrating engineering data and analysis using a multi-representation approach, Engineering with Computers 14: 93–114.

    Article  Google Scholar 

  • Poon, J and Maher, ML: 1996, Emergent behaviour in co-evolutionary design, in JS Gero and F Sudweeks (eds.), Artificial Intelligence in Design ‘86, Kluwer, Dordrecht, pp. 703–722.

    Chapter  Google Scholar 

  • Rosenman, MA: 1996, The generation of form using an evolutionary approach, in JS Gero and F Sudweeks (eds), Artificial Intelligence in Design ‘86, Kluwer, Dordrecht, pp. 643–662.

    Chapter  Google Scholar 

  • Rosenman, M and Gero, IS: 1999, Evolving designs by generating useful complex gene structures, in PJ Bentley (ed.), Evolutionary Design by Computers, Morgan Kaufmann, San Francisco, pp. 345–364.

    Google Scholar 

  • Rowbottom, A: 1999, Evolutionary art and form, in PJ Bentley (ed.), Evolutionary Design by Computers, Morgan Kaufmann, San Francisco, pp. 261–277.

    Google Scholar 

  • Sims, K: 1991, Artificial evolution for computer graphics, Computer Graphics 25 (4): 319–328.

    Article  MathSciNet  Google Scholar 

  • Suh, NP: 1990, The Principles of Design, Oxford University Press, New York.

    Google Scholar 

  • Todd, S and Latham, W: 1999, The mutation and growth of art by computers, in PJ Bentley (ed.), Evolutionary Design by Computers, Morgan Kaufmann, San Francisco, pp. 221–250.

    Google Scholar 

  • Tomiyama, T: 1995, A design process model that unifies general design theory and empirical findings, Proceedings of the 1995 Design Engineering Technical Conferences, DE-Vol. 83, ASME, New York, pp. 329–340.

    Google Scholar 

  • van Leeuwen, J and Wagter, I-I: 1998, A features framework for architectural information: Dynamic models for design, in JS Gero and F Sudweeks (eds), Artificial Intelligence in Design ‘88, Kluwer, Dordrecht, pp. 461–480.

    Chapter  Google Scholar 

  • Witbrock, M and Neil-Reilly, S: 1999, Evolving genetic art, in Pi Bentley, (ed.), Evolutionary Design by Computers, Morgan Kaufmann, San Francisco, pp. 251–260.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Chan, K.H., Frazer, J.H., Tang, MX. (2002). An Evolutionary Framework for Enhancing Design. In: Gero, J.S. (eds) Artificial Intelligence in Design ’02. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0795-4_19

Download citation

  • DOI: https://doi.org/10.1007/978-94-017-0795-4_19

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-6059-4

  • Online ISBN: 978-94-017-0795-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics