Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Goldberg D. (1989) Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA.
Lin L., Cao L., Wang J., and Zhang C. (2004) The Applications of Genetic Algorithms in Stock Market Data Mining Optimisation, Proceedings of Fifth International Conference on Data Mining, Text Mining and their Business App- lications, Malaga, Spain. September 15-17. 2004.
Obayashi S., Yamaguchi Y., and Nakamura T. (1997) Multiobjective genetic algorithm for multidisciplinary design of transonic wing platform. Journal of Aircraft, 34(5):690-693, 1997.
Ong Y. S., Nair P. B., Keane A. J., and Wong K. W. (2004) Surrogate-Assisted Evolutionary Optimization Frameworks for High-Fidelity Engineering Design Problems. In Y. Jin, editor, Knowledge Incorporation in Evolutionary Com- putation, Studies in Fuzziness and Soft Computing, pages 307-332. Springer, 2004.
Doǧan A. and Özgüner F. (2004) Genetic Algorithm Based Scheduling of Meta- Tasks with Stochastic Execution Times in Heterogeneous Computing Systems, Cluster Computing 7, 177-190, Kluwer Academic Publishers. Manufactured in The Netherlands, 2004.
Hacker H. A., Eddy H. and Lewis K. E. (2002) Efficient Global Optimization Uisng Hybrid Genetic Algorithms, 9th AIAA/IMMSO Symposium on Multidisciplinary Analysis and Optimization, 4-6 September 2002, Altanta, Georgia, AIAA 2002-5429.
Xu Z.-B., Leung, K.-S., Liang Y., and Leung Y. (2003) Efficiency speed-up strategies for evolutionary computation: fundamentals and fast-GAs, Applied Mathematics and Computation Vol. 142, 341-388, 2003.
Salami M. and Hendtlass T. (2003) A fast evaluation strategy for evolutionary algorithms. Applied Soft Computing, 2:156-173, 2003.
Potter M. A. and De Jong K. A. (1994) A cooperative Coevolutionary Approach to Function Optimisation, The Third Parallel Problem Solving From Nature, Jerusalem, Israel, pp. 249-257, 1994.
Ong Y. S. and Keane A. J. (2004) Meta-Lamarckian Learning in Memetic Algorithm, IEEE Transactions On Evolutionary Computation, Vol. 8, No. 2, pp. 99-110, April 2004.
Branke J. and Schmidt C. (2003) Fast convergence by means of fitness estimation. Soft Computing Journal, 2003.
Jones, D. R., Schinlau, M., and Welch, W. J. (1998) Efficient Global Opti- misation of Expensive Black-box Functions, Journal of Global Optimization, Vol. 13, pp. 455-492, 1998.
Ong Y. S., Nair P. B. and Keane A. J. (2003) Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling, AIAA Journal, Vol. 41, No. 4, pp. 687-696, 2003.
Song W. and Keane A. J. (2005) An efficient evolutionary optimisation frame- work applied to turbine blade firtree root local profiles, Structural and Multi- disciplinary Optimisation, Vol. 29 No. 5, 2005, pp. 382-390.
Jin Y. (2005) A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing. Vol. 9, No. 1, pp. 3-12, Springer, 2005.
Myers R. (2002) Response Surface Methodology: Process and Product Opti- mization Using Designed Experiments, John Wiley & Sons Inc. 2002.
Cressie, N. A. C. (1993) Statistics for Spatial Data, rev., Wiley, New York, 1993.
Kleijnen J. P. C. and Van Beers W. (2002) Kriging for interpolation in random simulation. Journal of the Operational Research Society, 54, No. 3, 255-262, 2003.
Ahn, J. A., Kim, H., Lee, D., Rho, O. (2001) Response Surface Method for Airfoil Design in Transonic Flow, Journal of Aircraft, Vol. 38, No. 2, 2001.
Simpson T.W. (1998) Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle, NASA/CR-1998-206935, ICASE report No. 98-16, 1998.
Venter, G., Haftka, R. T., Starners, J. H. Jr. (1998) Construction of Response Surface Approximations for Design Optimisation, AIAA Journal, Vol. 36, No. 12, 1998.
Bishop, C. (1995) Neural Networks for Pattern Recognition, Oxford University Press 1995.
Bandler, J. W., Cheng Q. S., Dakroury S. A., Mohamed A. S., Bakr M. H., Madsen, K. M. and Sondergaard J. (2004) Space Mapping: The State of the Art, IEEE Trasactions on Microwave Theory and Techniques. Vol. 52, No. 1, January 2004.
Sacks, J., Welch, W. J., Mitchell, J. J., Wynn, H. P. (1989) Design and Analysis of Computer Experiments, Statistical Science, Vol. 4, No. 4, 1989, pp. 409-435.
Guinta, A. A., Watson, L. T. (2003) A Comparison of Approximation Modelling Techniques: Polynomial versus Interpolating Models, AIAA-98-4758, 1998.
Daberkow, D. D., Marris, D. N. (1998) New Approaches to Conceptual and Preliminary Aircraft Design: A Comparative Assessment of a Neural Network Formulation and A Response Surface Methodology, AIAA, 1998 World Aviation Conference, September 28-30, 1998, Anaheim, CA, 1998.
Jin, R., Chen, W., Simpson, T. W. (2000) Comparative Studies of Metamod- elling Techniques under Multiple Modelling Criteria, AIAA-2000-4801, 2000.
Booker, A. J., Dennis, J. E., Frank, P. D., Serafini, D. B., Torczon, V., and Trosset, M. W. (1999) A Rigorous Framework for Optimization of Expensive Functions by Surrogates, Structural Optimization, Vol. 17, No. 1, 1999, pp. 1-13.
Alexandrov, N. M., Dennis, J. E. Jr., Lewis, R. M. (1997) A Trust Region Framework for Managing the Use of Approximation Models in Approximation, NASA/CR-201745, 1997.
Alexandrov, N. M. and Lewis, R. M. (2003) First-Order Frameworks for Managing Models in Engineering Optimisation, 1st International Workshop on Surrogate Modelling and Space Mapping for Engineering Optimisation, 11/16- 19/2000, TDU, 2003.
Guinta, A. A. and Eldred, M. S. (2000) Implementation of a Trust Region Model Management Strategy in the Dakota Optimisation Toolkit, AIAA-2000-4935, 2000.
Sellar, R. S., Batill, S. M., Renaud, J. E. (2003) Response Surface Based, Con- current Subspace Optimisation for Multidisciplinary System Design, 2003.
Wujek, B. A. and Renaud, J. E. (1998) New Adaptive Move-limit Manage- ment Strategy for Approximate Optimization, Part 1, AIAA Journal, Vol. 36, No. 10, 1998, pp. 1911-1921.
Alexandrov, N. M. (1998) On Managing the Use of Surrogates in General Non- linear Optimization and MDO, AIAA-98-4798, 1998.
Robinson, G. M. and Keane, A. J. (1999) A Case for Multi-level Optimisation in Aeronautical Design, Aeronautical Journal, Vol. 103, 1999, pp. 481-485.
Nair, P. B. and Keane, A. J. (1998) Combining Approximation Concepts with Genetic Algorithm-based Structure Optimisation Procedure, 1998.
Ratle, W. (1998) Accelerating the Convergence of Evolutionary Algorithms by Fitness Landscape Approximation, Parallel Problem Solving from Nature V, 1998, pp. 87-96.
El-Beltagy, M. A. and Keane, A. J. (1999) Evolutionary Optimisation for Com- putationally Expensive Problems Using Gaussian Processes, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO99), Morgan Kaufman, 1999, pp. 196-203.
Liang, K. H., Yao, X., Newton, C. (2000) Evolutionary Search of Approximated N-dimensional Landscapes, International Journal of Knowledge-Based Intelli- gent Engineering Systems, Vol. 4, No. 3, 2000, pp. 172-183.
Jin, Y., Olhofer, M. and Sendhoff, B. (2000) A Framework for Evolutionary Optimisation with Approximate Fitness Functions, IEEE Transactions on Evo- lutionary Computation, 2000.
Morris, M.D., Mitchell, T.J. and Ylvisaker, D. (1993) Baysian Design and Analy- sis of Computer Experiments: Use of Derivatives in Surface Prediction, Techno- metrics, Vol. 35, 1993, pp. 243-255.
Song W., Keane A.J., Rees J., Bhaskar A. and Bagnall S. (2002) Local Shape Optimisation of a Firtree root using NURBS, 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, Georgia 4-6 Sep 2002.
Song W. and Keane A.J. (2005) A New Hybrid Update Scheme for an Evolutionary Search Strategy Using Genetic Algorithm and Kriging, 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, 13th AIAA/ASME/AHS Adaptive Structures Conference 7t, Austin, Texas, Apr. 18-21, 2005.
Fluent (2006) http://www.fluent.com, 2006.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Song, W. (2007). Evolutionary Shape Optimization Using Gaussian Processes. In: Yang, S., Ong, YS., Jin, Y. (eds) Evolutionary Computation in Dynamic and Uncertain Environments. Studies in Computational Intelligence, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49774-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-49774-5_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49772-1
Online ISBN: 978-3-540-49774-5
eBook Packages: EngineeringEngineering (R0)