Creative Conceptual Design Based on Evolutionary DNA Computing Technique
Abstract
Creative conceptual design is an important area in computer aided innovation. Typical design methodology includes exploration and optimization by evolutionary techniques such as EC and swarm intelligence. Although there are many proposed algorithms and applications for creative design by these techniques, the computing models are implemented mostly by traditional von Neumann’s architecture. On the other hand, the possibility of using DNA as a computing technique arouses wide interests in recent years with huge built-in parallel computing nature and ability to solve NP complete problems. This new computing technique is performed by biological operations on DNA molecules rather than chips. The purpose of this paper is to propose a simulated evolutionary DNA computing model and integrate DNA computing with creative conceptual design. The proposed technique will apply for large scale, high parallel design problems potentially.
Keywords
Evolution conceptual design DNA computing innovationReferences
- 1.Adleman, L.M.: Molecular Computation of Solutions to Combinatorial Problems. Science 266(5187), 1021–1023 (1994)CrossRefGoogle Scholar
- 2.Bentley, P.J.: Generic Evolutionary Design of Solid Objects using a Genetic Algorithm, Doctoral Thesis, the University of Huddersfild (1996)Google Scholar
- 3.Cho, S.-B.: Towards creative evolutionary systems with interactive genetic algorithm. Applied Intelligence 16, 129–138 (2002)CrossRefMATHGoogle Scholar
- 4.Ding, Y.S.: Computational Intelligence: Theory, Technique and Applications. Science Press, Beijing (2004)Google Scholar
- 5.Ezziane, Z.: DNA computing: applications and challenges. Nanotechnology 17, R27–R39 (2006)CrossRefGoogle Scholar
- 6.Yan, H., Zhang, X., Shen, Z., et al.: A robust DNA mechanical device controlled by hybridization topology. Nature 415(3), 62–65 (2002)CrossRefGoogle Scholar
- 7.Tom, H.: Formal language theory and DNA: an analysis of the generative capacity of specific recombinant behaviors. Bulletin of Mathematical Biology 49(6), 737–759 (1987)MathSciNetCrossRefMATHGoogle Scholar
- 8.Janet, L.K., Linda, M.W.: Case-Based Creative Design. In: Proceedings Kolodner 1993 Case-based Creativity, AAAI Spring Symposium on AI and Creativity, pp. 50–57. Springer, Stanford (1993)Google Scholar
- 9.Jonoska, N., Karl, S.A., Saito, M.: Three dimensional DNA structures in computing. Biosystems 52, 143–153 (1999)CrossRefGoogle Scholar
- 10.Sakamoto, K., et al.: Molecular Computation by DNA Hairpin Formation. Science 288, 1223–1226 (2000)CrossRefGoogle Scholar
- 11.Li, R.-H., Yu, W.: An Exploration of the Principles of DNA Computation. Chinese J. Computers 24(9), 972–978 (2001)MathSciNetGoogle Scholar
- 12.Lipton, R.J.: DNA solution of hard computational problems. Science 268(28), 542–545 (1995)CrossRefGoogle Scholar
- 13.Rajeev, M., Prabhakar, R.: Randomized Algorithms. Cambridge University Press, USA (1995)MATHGoogle Scholar
- 14.Bakar, R.B.A., Watada, J., Pedrycz, W.: DNA approach to solve clustering problem based on a mutual order. BioSystems 91, 1–12 (2008)CrossRefGoogle Scholar
- 15.Deaton, R., Garzon, M., Rose, J., et al.: DNA Computing: A Review. Fundamenta Informaticae 30, 23–41 (1997)MATHGoogle Scholar
- 16.Arida, S.: Contextualizing generative design, Thesis of Damascus University (2004)Google Scholar
- 17.Xu, J., Zhang, S.-M., Fan, Y.-K., et al.: DNA Computer Principle, Advances and Di_culties (III): The Structure and Character of ”Data” in DNA Computing. Chinese Journal of Computers 30(6), 869–880 (2007)MathSciNetGoogle Scholar