Review of Metamodeling Techniques in Support of Engineering Design Optimization

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Koch, Statistical Approximations for Multidisciplinary Design Optimization: The Problem of Size, J. Aircr., 36, 275, 10.2514/2.2435

Barthelemy, Approximation Concepts for Optimal Structural Design—A Review, Struct. Optim., 5, 129, 10.1007/BF01743349

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Simpson, Metamodels for Computer-Based Engineering Design: Survey and Recommendations, Eng. Comput., 17, 129, 10.1007/PL00007198

Simpson, Approximation Methods in Multidisciplinary Analysis and Optimization: A Panel Discussion, Struct. Multidiscip. Optim., 27, 302

Ullman, Toward the Ideal Mechanical Engineering Design Support System, Res. Eng. Des., 13, 55, 10.1007/s00163-001-0007-4

Myers, Response Surface Methodology: Process and Product Optimization Using Designed Experiments

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Mitchell, An Algorithm for the Construction of “D-Optimal” Experimental Designs, Technometrics, 16, 203, 10.2307/1267940

Giunta, Multidisciplinary Optimization of a Supersonic Transport Using Design of Experiments Theory and Response Surface Modeling, Aeronaut. J., 101, 347, 10.1017/S0001924000066045

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Koehler, Computer Experiments, Handbook of Statistics, 261

Currin, Bayesian Prediction of Deterministic Functions, With Applications to the Design and Analysis of Computer Experiments, J. Am. Stat. Assoc., 86, 953, 10.2307/2290511

Johnson, Minimax and Maximin Distance Designs, J. Stat. Plan. Infer., 26, 131, 10.1016/0378-3758(90)90122-B

Taguchi, Taguchi Methods: Design of Experiments

Owen, Orthogonal Arrays for Computer Experiments, Integration, and Visualization, Stat. Sin., 2, 439

Hedayat, Orthogonal Arrays: Theory and Applications, 10.1007/978-1-4612-1478-6

McKay, A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code, Technometrics, 21, 239, 10.2307/1268522

Iman, Small Sensitivity Analysis Techniques for Computer Models With an Application to Risk Assessment, Commun. Stat: Theory Meth., A9, 1749, 10.1080/03610928008827996

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Park, Optimal Latin-hypercube Designs for Computer Experiments, J. Stat. Plan. Infer., 39, 95, 10.1016/0378-3758(94)90115-5

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Kalagnanam, An Efficient Sampling Technique for Off-Line Quality Control, Technometrics, 39, 308, 10.2307/1271135

Meckesheimer, Computationally Inexpensive Metamodel Assessment Strategies, AIAA J., 40, 2053, 10.2514/2.1538

Fang, Uniform Design: Theory and Application, Technometrics, 39, 237, 10.1080/00401706.2000.10486045

Chen, A Review on Design, Modeling and Applications of Computer Experiments, IIE Trans., 38, 273, 10.1080/07408170500232495

Simpson, Sampling Strategies for Computer Experiments: Design and Analysis, Int. J. Reliab. Appl., 2, 209

Au, A New Adaptive Importance Sampling Scheme for Reliability Calculations, Struct. Safety, 21, 135, 10.1016/S0167-4730(99)00014-4

Zou, An Indicator Response Surface-Based Monte Carlo Method for Efficient Component and System Reliability Analysis, Proceedings ASME 2003 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2003/DAC-48708

Zou, Reliability Analysis of Automotive Body-Door Subsystem, Reliab. Eng. Syst. Saf., 78, 315, 10.1016/S0951-8320(02)00178-3

Kloess, Probabilistic Analysis of An Automotive Body-Door System, Int. J. Veh. Des., 34, 101, 10.1504/IJVD.2004.003896

Ditlevsen, Solution of A Class of Load Combination Problems by Directional Simulation, Struct. Safety, 4, 95, 10.1016/0167-4730(86)90025-1

Walker, Practical Application of Variance Reduction Techniques in Probabilistic Assessments, Proceedings 2nd International Conference on Radioactive Waste Management

Nie, Finite Element-Based Structural Reliability Assessment Using Efficient Directional Simulation, J. Eng. Mech., 131, 259, 10.1061/(ASCE)0733-9399(2005)131:3(259)

Wang, Mode-Pursuing Sampling Method for Global Optimization on Expensive Black-box Functions, Eng. Optimiz., 36, 419, 10.1080/03052150410001686486

Shan, An Efficient Pareto Set Identification Approach for Multi-objective Optimization on Black-box Functions, J. Mech. Des., 127, 866, 10.1115/1.1904639

Wang, Reliability Assessment Using Discriminative Sampling and Metamodeling, SAE Trans., 291

Fu, A Random-Discretization Based Monte Carlo Sampling Method and Its Applications, Methodol. Comput. Appl. Probab., 4, 5, 10.1023/A:1015790929604

Lin, Y. , 2004, “An Efficient Robust Concept Exploration Method and Sequential Exploratory Experimental Design,” Ph.D. dissertation thesis, Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA.

Jin, An Efficient Algorithm for Constructing Optimal Design of Computer Experiments, J. Stat. Plan. Infer., 134, 268, 10.1016/j.jspi.2004.02.014

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Sasena, Adaptive Experimental Design Applied to An Ergonomics Testing Procedure, Proceedings ASME 2002 Design Engineering Technical Conferences and Computer and Information in Engineering Conference, 10.1115/DETC2002/DAC-34091

Wang, Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points, J. Mech. Des., 125, 210, 10.1115/1.1561044

Wang, Fuzzy Clustering Based Hierarchical Metamodeling for Space Reduction and Design Optimization, Eng. Optimiz., 36, 313, 10.1080/03052150310001639911

Jin, On Sequential Sampling for Global Metamodeling for in Engineering Design, Proceedings ASME 2002 Design Engineering Technical Conferences and Computer and Information in Engineering Conference, 10.1115/DETC2002/DAC-34092

Sacks, Designs for Computer Experiments, Technometrics, 31, 41, 10.2307/1270363

Cresssie, Spatial Prediction and Ordinary Kriging, Math. Geol., 20, 405, 10.1007/BF00892986

Papadrakakis, Structural Optimization Using Evolution Strategies and Neural Networks, Comput. Methods Appl. Mech. Eng., 156, 309

Dyn, Numerical Procedures for Surface Fitting of Scattered Data by Radial Basis Functions, SIAM (Soc. Ind. Appl. Math.) J. Sci. Stat. Comput., 7, 639, 10.1137/0907043

Fang, Global Response Approximation With Radial Basis Functions, Eng. Optimiz., 38, 407, 10.1080/03052150500422294

Friedman, Multivariate Adaptive Regressive Splines, Ann. Stat., 19, 1, 10.1214/aos/1176347963

De Boor, On Multivariate Polynomial Interpolation, Constructive Approx., 6, 287, 10.1007/BF01890412

Langley, Applications of Machine Learning and Rule Induction, Commun. ACM, 38, 55

Varadarajan, Robust Concept Exploration of Propulsion Systems With Enhanced Model Approximation Capabilities, Eng. Optimiz., 32, 309, 10.1080/03052150008941302

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Simpson, Kriging Metamodels for Global Approximation in Simulation-based Multidisciplinary Design Optimization, AIAA J., 39, 2233, 10.2514/2.1234

Wang, Gaussian Process Metamodels for Efficient Probabilistic Design in Complex Engineering Design Spaces, Proceedings ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference

Qian, Building Surrogate Models Based on Detailed and Approximate Simulations, Proceedings ASME 2004 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2004-57486

Martin, Use of Kriging Models to Approximate Deterministic Computer Models, AIAA J., 43, 853, 10.2514/1.8650

Li, Penalized Likelihood Kriging Model for Analysis of Computer Experiments, Proceedings ASME 2003 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2003/DAC-48758

Kleijnen, Kriging for Interpolation in Random Simulation, J. Oper. Res. Soc. Jpn., 54, 255

Daberkow, An Investigation of Metamodeling Techniques for Complex Systems Design, Proceedings 9th AIAA/USFA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 10.2514/6.2002-5457

Lophaven, S. N., Nielsen, H. B., and Søndergaard, J., 2002, DACE—A Matlab Kriging Toolbox—Version 2.0, Informatics and Mathematical Modelling, Technical University of Denmark, Kgs. Lyngby, Denmark, Rep. No. IMM-REP-2002-12.

Clarke, Analysis of Support Vector Regression for Approximation of Complex Engineering Analyses, J. Mech. Des., 127, 1077, 10.1115/1.1897403

Pérez, Adaptive Experimental Design for Construction of Response Surface Approximations, AIAA J., 40, 2495, 10.2514/2.1593

Mullur, Extended Radial Basis Functions: More Flexible and Effective Metamodeling, AIAA J., 43, 1306, 10.2514/1.11292

Turner, Selecting an Appropriate Metamodel: The Case for NURBS Meamodels, Proceedings ASME 2005 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2005-85043

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Koehler, Estimating the Response, Derivatives, and Transmitted Variance Using Computer Experiments, Proceedings 1997 Symposium on the Interface of Computing Science and Statistics

Toropov, Multi-parameter Structural Optimization Using FEM and Multipoint Approximation, Struct. Multidiscip. Optim., 6, 7, 10.1007/BF01743169

Wang, Multivariate Hermite Approximation for Design Optimization, Int. J. Numer. Methods Eng., 39, 787, 10.1002/(SICI)1097-0207(19960315)39:5<787::AID-NME881>3.0.CO;2-5

Rasmussen, Nonlinear Programming by Cumulative Approximation Refinement, Struct. Optim., 15, 1, 10.1007/BF01197431

Shin, A Global Structural Optimization Technique Using an Interval Method, Struct. Multidiscip. Optim., 22, 351, 10.1007/s00158-001-0155-1

Huber, Analysis of Simulation Models with Fuzzy Graph Based Metamodeling, Perform. Eval., 27–28, 473

Madu, A Fuzzy Theoretic Approach to Simulation Metamodeling, Appl. Math. Lett., 8, 35, 10.1016/0893-9659(95)00082-2

Kleijnen, Design and Analysis of Monte Carlo Experiments, Handbook of Computational Statistics: Concepts and Fundamentals, 10.1007/978-3-642-21551-3_18

Giunta, Noisy Aerodynamic Response and Smooth Approximations in HSCT Design, Proceedings 5th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 7–9 Sept.

Madsen, Response Surface Techniques for Diffuser Shape Optimization, AIAA J., 38, 1512, 10.2514/2.1160

Jin, The Use of Metamodeling Techniques for Optimization Under Uncertainty, Struct. Multidiscip. Optim., 25, 99, 10.1007/s00158-002-0277-0

van Beers, Kriging Interpolation in Simulation: A Survey, Proceedings of the 2004 Winter Simulation Conference, 113

Oberkampf, Validation Methodology in Computational Fluid Dynamics, Proceedings Fluids 2000, 10.2514/6.2000-2549

Roache, Verification and Validation in Computational Science and Engineering

Meckesheimer, M. , 2001, “A Framework For Metamodel-Based Design: Subsystem Metamodel Assessment and Implementation Issues,” Ph.D. dissertation thesis, Industrial Engineering, The Pennsylvania State University, University Park, PA.

Mitchell, Bayesian Design and Analysis of Computer Experiments: Two Examples, Stat. Sin., 2, 359

Montgomery, Design and Analysis of Experiments

Wong, 30 Years of Multidimensional Multivariate Visualization, Scientific Visualization—Overviews, Methodologies and Techniques, 3

Keim, Visualization Techniques for Mining Large Databases: A Comparison, IEEE Trans. Knowl. Data Eng., 8, 923, 10.1109/69.553159

Winer, Development of Visual Design Steering as an Aid in Large-scale Multidisciplinary Design Optimization. Part II: Method Validation, Struct. Multidiscip. Optim., 23, 425, 10.1007/s00158-002-0204-4

Winer, Development of Visual Design Steering as an Aid in Large-scale Multidisciplinary Design Optimization. Part I: Method Development, Struct. Multidiscip. Optim., 23, 412, 10.1007/s00158-002-0203-5

Eddy, Visualization of Multi-dimensional Design and Optimization Data Using Cloud Visualization, Proceedings ASME 2002 Design Engineering Technical Conference and Computers and Information in Engineering Conference

Kodiyalam, High Performance Computing and Surrogate Modeling for Rapid Visualization with Multidisciplinary Optimization, AIAA J., 42, 2347, 10.2514/1.1997

Simpson, Multidisciplinary Design Optimization, Aerosp. Am., 12, 34

Stump, Multidimensional Design and Visualization and Its Application to a Design By Shopping Paradigm, Proceedings 9th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 10.2514/6.2002-5622

Eddy, Multidimensional Design Visualization in Multiobjective Optimization, Proceedings 9th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 10.2514/6.2002-5621

Mattson, Concept Selection Using s-Pareto Frontiers, AIAA J., 41, 1190, 10.2514/2.2063

Ligetti, Metamodel-Driven Design Optimization Using Integrative Graphical Design Interfaces: Results From a Job-Shop Manufacturing Simulation Experiment, J. Comput. Inf. Sci. Eng., 5, 8, 10.1115/1.1794698

Ligetti, Assessing the Impact of Graphical Design Interfaces on Design Efficiency and Effectiveness, J. Comput. Inf. Sci. Eng., 3, 144, 10.1115/1.1583757

Simpson, Metamodel-Driven Interfaces for Engineering Design: Impact of Delay and Problem Size on User Performance, Proceedings 1st AIAA Multidisciplinary Design Optimization Specialist Conference, 18–21 Apr., 10.2514/6.2005-2060

Box, Evolutionary Operation: A Statistical Method for Process Management

Welch, Screening, Predicting, and Computer Experiments, Technometrics, 34, 15, 10.2307/1269548

Balabanov, Reasonable design space approach to response surface approximation, J. Aircr., 36, 308, 10.2514/2.2438

Chen, Statistical Experimentation Methods for Achieving Affordable Concurrent Systems Design, AIAA J., 35, 893, 10.2514/2.7464

Wujek, New Adaptive Move-Limit Management Strategy for Approximate Optimization, Part 1, AIAA J., 36, 1911, 10.2514/2.285

Wujek, New Adaptive Move-Limit Management Strategy for Approximate Optimization, Part 2, AIAA J., 36, 1922, 10.2514/2.287

Toropov, Refinements in the Multi-Point Approximation Method to Reduce the Effects of Noisy Structural Responses, Proceedings 6th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 10.2514/6.1996-4087

Alexandrov, A Trust Region Framework for Managing the Use of Approximation Models in Optimization, Struct. Optim., 15, 16, 10.1007/BF01197433

Rodríguez, Trust Region Augmented Lagrangian Methods for Sequential Response Surface Approximation and Optimization, J. Mech. Des., 120, 58, 10.1115/1.2826677

Renaud, Approximation in Non-hierarchical System Optimization, AIAA J., 32, 198, 10.2514/3.11967

Wang, Adaptive Response Surface Method—A Global Optimization Scheme for Computation-Intensive Design Problems, Eng. Optimiz., 33, 707, 10.1080/03052150108940940

Shan, Space Exploration and Global Optimization for Computationally Intensive Design Problems: A Rough Set Based Approach, Struct. Multidiscip. Optim., 28, 427, 10.1007/s00158-004-0448-2

Wang, Design Space Reduction for Multi-objective Optimization and Robust Design Optimization Problems, SAE Trans., 101

Li, Fixture Configuration Design for Sheet Metal Laser Welding With a Two-Stage Response Surface Methodology, Proceedings ASME 2001 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2001/DAC-21096

Dennis, Managing Approximation Models in Optimization, Multidisciplinary Design Optimization: State of the Art

Osio, An Engineering Design Methodology With Multistage Bayesian Surrogates and Optimal Sampling, Res. Eng. Des., 8, 189, 10.1007/BF01597226

Booker, A Rigorous Framework for Optimization of Expensive Functions by Surrogates, Struct. Optim., 17, 1, 10.1007/s001580050031

Rodríguez, Sequential Approximate Optimization Using Variable Fidelity Response Surface Approximations, Struct. Multidiscip. Optim., 22, 24, 10.1007/s001580100122

Schonlau, Global Versus Local Search in Constrained Optimization of Computer Models, New Development and Applications in Experimental Design, 11

Sasena, Global Optimization of Problems With Disconnected Feasible Regions Via Surrogate Modeling, Proceedings 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 10.2514/6.2002-5573

Gelsey, Using Modeling Knowledge to Guide Design Space Search, Artif. Intell., 100, 1

Shan, Failure Surface Frontier for Reliability Assessment on Expensive Performance Function, J. Mech. Des., 128, 1227, 10.1115/1.2337311

Jones, Efficient Global Optimization of Expensive Black Box Functions, J. Global Optim., 13, 455, 10.1023/A:1008306431147

Hirokawa, Voronoi Diagram Based Blending of Quadratic Response Surfaces for Cumulative Global Optimization, Proceedings 9th AIAA/ISSMO Symposium on Multi-Disciplinary Analysis and Optimization, 10.2514/6.2002-5460

Hacker, Tuning a Hybrid Optimization Algorithm by Determining the Modality of the Design Space, Proceedings ASME 2001 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2001/DAC-21093

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Chen, A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors, J. Mech. Des., 118, 478, 10.1115/1.2826915

Chen, An Affordable Approach for Robust Design of Thick Laminated Composite Structure, Optim. Eng., 1, 305, 10.1023/A:1010078107194

Booker, Reliability Based Design Optimization Using Design Explorer, Optim. Eng., 5, 179, 10.1023/B:OPTE.0000033374.31878.15

Youn, Selecting Probabilistic Approaches for Reliability-Based Design Optimization, AIAA J., 42, 124, 10.2514/1.9036

Sobieszczanski-Sobieski, Multidisciplinary Aerospace Design Optimization: Survey of Recent Developments, Struct. Optim., 14, 1, 10.1007/BF01197554

Golovidov, A Flexible, Object-based Implementation of Approximation Models in an MDO Framework, Design Optimization: Int. J. Product Process Improvement, 1, 388

Batill, Framework for Multidisciplinary Design Based on Response-Surface Approximations, J. Aircr., 36, 287, 10.2514/2.2436

Sobieski, Collaborative Optimization Using Response Surface Estimation, AIAA J., 38, 1931, 10.2514/2.847

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Plackett, The Design of Optimum Multifactorial Experiments, Biometrika, 33, 305, 10.2307/2332195

Otto, A Surrogate Approach to the Experimental Optimization of Multi-element Airfoils, Proceedings 6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization

Otto, Computer Simulation Surrogates for Optimization: Application of Trapezoidal Ducts and Axisymmetric Bodies, Proceedings ASME International Mechanical Engineering Conference and Exposition

Wang, Thermofluid Optimization of a Heated Helicopter Engine Cooling Bay Surface, Can. Aeronautics Space J., 49, 73, 10.5589/q03-006

Yang, Metamodeling Development for Vehicle Frontal Impact Simulation, Proceedings ASME 2001 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/1.1906264

Redhe, An Investigation of Structural Optimization in Crashworthiness Design Using a Stochastic Approach, Struct. Multidiscip. Optim., 27, 446

Giunta, Wing Design for a High-Speed Civil Transport Using a Design of Experiments Methodology, Proceedings 6th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization

Wang, Design Optimization of a Complex Mechanical System Using Adaptive Response Surface Method, Trans. Can. Soc. Mech. Eng., 24, 295, 10.1139/tcsme-2000-0024

Ejakov, Robustness and Performance Optimization of Engine Bearing System Using Computer Model and Surrogate Noise, Proceedings ASME 2004 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 10.1115/DETC2004-57327

Srivastava, A Method for Using Legacy Data for Metamodel-Based Design of Large-Scale Systems, Struct. Multidiscip. Optim., 28, 146

Leary, A Knowledge-Based Approach To Response Surface Modelling in Multifidelity Optimization, J. Global Optim., 26, 297, 10.1023/A:1023283917997

Farhang Mehr, Meta-Modeling of Multi-Response Engineering Simulations, Proceedings 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 10.2514/6.2004-4485

Sahin, Better Optimization of Nonlinear Uncertain Systems (Bonus): A New Algorithm for Stochastic Programming Using Reweighting Through Kernel Density Estimation, Ann. Operat. Res., 132, 47, 10.1023/B:ANOR.0000045276.18995.c8

Ellman, Multi-level Modeling for Engineering Design Optimization, Artif. Intell. Eng. Des. Anal. Manuf., 11, 1

Leoni, Bayesian Surrogates for Integrating Numerical, Analytical and Experimental Data: Application to Inverse Heat Transfer in Wearable Computers, IEEE Trans. Compon. Packag. Technol., 23, 23, 10.1109/6144.833038

Bakr, Review of the Space Mapping Approach to Engineering Optimization and Modeling, Optim. Eng., 1, 241, 10.1023/A:1010000106286

Campbell, Qualitative and Quantitative Sequential Sampling, Proceedings of the ASME 2006 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference

Romero, On Adaptive Sampling for Metamodels in Simulation-based Design and Optimization, Proceedings of the ASME 2006 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference

Koch, Design for Six Sigma Through Robust Optimization, Struct. Multidiscip. Optim., 26, 235