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Abstract

Generic evolutionary design means the creation of a range of different designs by evolution. This paper introduces generic evolutionary design by a computer, describing a system capable of the evolution of a wide range of solid object designs from scratch, using a genetic algorithm.

The paper reviews relevant literature, and outlines a number of advances necessitated by the development of the system, including: a new generic representation of solid objects, a new multiobjective fitness ranking method, and variable-length chromosomes. A library of modular evaluation software is also described, which allows a user to define new design problems quickly and easily by picking combinations of modules to guide the evolution of designs.

Finally, the feasibility of generic evolutionary design by a computer is demonstrated by presenting the successful evolution of both conventional and unconventional designs for a range of different solid-object design tasks, e.g. tables, heatsinks, prisms, boat hulls, aerodynamic cars.

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References

  1. Bentley, P. J., 1996, Generic Evolutionary Design of Solid Objects using a Genetic Algorithm. Ph.D. Thesis, University of Huddersfield, Huddersfield, UK.

    Google Scholar 

  2. Bentley, P. J. & Wakefield, J. P., 1996a, The Evolution of Solid Object Designs using Genetic Algorithms. Modern Heuristic Search Methods, John Wiley & Sons Inc., Ch 12, 197-211.

    Google Scholar 

  3. Bentley, P. J. & Wakefield, J. P., 1996b, Generic Representation of Solid Geometry for Genetic Search. Microcomputers in Civil Engineering 11:3, 153–161.

    Article  Google Scholar 

  4. Bentley, P. J. & Wakefield, J. P., 1996c, Hierarchical Crossover in Genetic Algorithms. Proceedings of the 1st On-line Workshop on Soft Computing (WSCI), Nagoya University, Japan, 37-42.

    Google Scholar 

  5. Culley, S. J. and Wallace, A. P., 1994, Optimum Design of Assemblies with Standard Components. Proc. of Adaptive Computing in Engineering Design and Control — ′94, Plymouth, 163-168.

    Google Scholar 

  6. Dawkins, R. 1986, The Blind Watchmaker, Longman Scientific & Technical Pub.

    Google Scholar 

  7. Dyer, M. Flower, M. and Hodges, J., 1986, ‘EDISON’: an engincering design invention system operating naively. Artificial Intelligence 1, 36-44.

    Google Scholar 

  8. Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization & Machine Learning, Addison-Wesley.

    Google Scholar 

  9. Holland, J. H., 1992, Genetic Algorithms. Scientific American, 66-72.

    Google Scholar 

  10. Parmce, I C & Denham, M J, 1994, The Integration of Adaptive Search Techniques with Current Engineering Design Practice. Proc. of Adaptive Computing in Engineering Design and Control — ′94, Plymouth, 1-13.

    Google Scholar 

  11. Pham, D. T. & Yang, Y., 1993, A genetic algorithm based preliminary design system. Journal of Automobile Engineers v207:D2, 127–133.

    Article  Google Scholar 

  12. Rosenman, M. A., 1996, A Growth Model for Form Generation Using a Hierarchical Evolutionary Approach. Microcomputers in Civil Engineering 11:3, 163–174.

    Article  Google Scholar 

  13. Todd, S. & Latham, W., 1992, Evolutionary Art and Computers, Academic Press.

    Google Scholar 

  14. Tong, S.S., 1992, Integration of symbolic and numerical methods for optimizing complex engineering systems. IFIP Transactions (Computer Science and Technology) vA-2, 3–20.

    Google Scholar 

  15. Williams, B. C., 1990, Visualising potential interactions: constructing novel devices from first priciples. Proc. of Eighth National Conference on Artificial Intelligence (AAAI-90), Boston, Mass.

    Google Scholar 

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Correspondence to P. J. Bentley .

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© 1998 Springer-Verlag London

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Bentley, P.J., Wakefield, J.P. (1998). Generic Evolutionary Design. In: Chawdhry, P.K., Roy, R., Pant, R.K. (eds) Soft Computing in Engineering Design and Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-0427-8_31

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  • DOI: https://doi.org/10.1007/978-1-4471-0427-8_31

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76214-0

  • Online ISBN: 978-1-4471-0427-8

  • eBook Packages: Springer Book Archive

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