Evolutionary Shape Optimization Using Gaussian Processes

[1]  Yaochu Jin,et al.  A comprehensive survey of fitness approximation in evolutionary computation , 2005, Soft Comput..

[2]  Andy J. Keane,et al.  A new hybrid updating scheme for an evolutionary search strategy using genetic algorithms and kriging , 2005 .

[3]  Mehrdad Salami,et al.  A fast evaluation strategy for evolutionary algorithms , 2003, Appl. Soft Comput..

[4]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[5]  T. W. Layne,et al.  A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models , 1998 .

[6]  Jürgen Branke,et al.  Faster convergence by means of fitness estimation , 2005, Soft Comput..

[7]  Kenneth A. De Jong,et al.  A Cooperative Coevolutionary Approach to Function Optimization , 1994, PPSN.

[8]  Thomas J. Santner,et al.  The Design and Analysis of Computer Experiments , 2003, Springer Series in Statistics.

[9]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[10]  Andy J. Keane,et al.  A case for multi-level optimisation in aeronautical design , 1999, The Aeronautical Journal (1968).

[11]  Timothy W. Simpson,et al.  Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle , 1998 .

[12]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[13]  A. Keane,et al.  Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling , 2003 .

[14]  Kok Wai Wong,et al.  Surrogate-Assisted Evolutionary Optimization Frameworks for High-Fidelity Engineering Design Problems , 2005 .

[15]  T. J. Mitchell,et al.  Bayesian design and analysis of computer experiments: Use of derivatives in surface prediction , 1993 .

[16]  Shigeru Obayashi,et al.  Multiobjective Genetic Algorithm for Multidisciplinary Design of Transonic Wing Planform , 1997 .

[17]  N. M. Alexandrov,et al.  A trust-region framework for managing the use of approximation models in optimization , 1997 .

[18]  Kemper Lewis,et al.  EFFICIENT GLOBAL OPTIMIZATION USING HYBRID GENETIC ALGORITHMS , 2002 .

[19]  Dimitri N. Mavris,et al.  New Approaches to Conceptual and Preliminary Aircraft Design: A Comparative Assessment of a Neural Network Formulation and a Response Surface Methodology , 1998 .

[20]  T. Simpson,et al.  Comparative studies of metamodeling techniques under multiple modeling criteria , 2000 .

[21]  John E. Renaud,et al.  Response surface based, concurrent subspace optimization for multidisciplinary system design , 1996 .

[22]  Andy J. Keane,et al.  Combining approximation concepts with genetic algorithm-based structural optimization procedures , 1998 .

[23]  Dong-Ho Lee,et al.  Response Surface Method for Airfoil Design in Transonic Flow , 2001 .

[24]  Andy J. Keane,et al.  LOCAL SHAPE OPTIMISATION OF TURBINE DISC FIRTREES USING NURBS , 2002 .

[25]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[26]  Atakan Dogan,et al.  Genetic Algorithm Based Scheduling of Meta-Tasks with Stochastic Execution Times in Heterogeneous Computing Systemst1 , 2004, Cluster Computing.

[27]  M. Natalia On Managing the Use of Surrogates in General Nonlinear Optimization and MDO , 1998 .

[28]  J.W. Bandler,et al.  Space mapping: the state of the art , 2004, IEEE Transactions on Microwave Theory and Techniques.

[29]  T. Simpson,et al.  Comparative studies of metamodelling techniques under multiple modelling criteria , 2001 .

[30]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[31]  J. Renaud,et al.  New Adaptive Move-Limit Management Strategy for Approximate Optimization, Part 2 , 1998 .

[32]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[33]  Kwong-Sak Leung,et al.  Efficiency speed-up strategies for evolutionary computation: fundamentals and fast-GAs , 2003, Appl. Math. Comput..

[34]  Jack P. C. Kleijnen,et al.  Kriging for interpolation in random simulation , 2003, J. Oper. Res. Soc..

[35]  Michael S. Eldred,et al.  IMPLEMENTATION OF A TRUST REGION MODEL MANAGEMENT STRATEGY IN THE DAKOTA OPTIMIZATION TOOLKIT , 2000 .

[36]  L. Lin,et al.  The Applications Of Genetic Algorithms InStock Market Data Mining Optimisation , 2004 .

[37]  Andy J. Keane,et al.  An efficient evolutionary optimisation framework applied to turbine blade firtree root local profiles , 2005 .

[38]  J. H. Starnes,et al.  Construction of Response Surface Approximations for Design Optimization , 1998 .

[39]  Andy J. Keane,et al.  Meta-Lamarckian learning in memetic algorithms , 2004, IEEE Transactions on Evolutionary Computation.

[40]  A. J. Booker,et al.  A rigorous framework for optimization of expensive functions by surrogates , 1998 .

[41]  Alain Ratle,et al.  Accelerating the Convergence of Evolutionary Algorithms by Fitness Landscape Approximation , 1998, PPSN.