Efficient space-filling and non-collapsing sequential design strategies for simulation-based modeling

No abstract is available for this paper.

• Publication year

  2011

• Venue

  European Journal of Operational Research

• Publication date

  2011-11-01

• Fields of study

  Chemistry, Computer Science, Engineering

• Identifiers
  DOI 10.1016/j.ejor.2011.05.032
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference

  2013cited by this paper
• A Novel Hybrid Sequential Design Strategy for Global Surrogate Modeling of Computer Experiments

  2011cited by this paper
• Stochastic radial basis function algorithms for large-scale optimization involving expensive black-box objective and constraint functions

  2011cited by this paper
• A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design

  2010cited by this paper
• An algorithm for fast optimal Latin hypercube design of experiments

  2010influential reference
• Nested Latin hypercube designs

  2009cited by this paper
• Space-filling sequential design strategies for adaptive surrogate modelling

  2009influential reference
• A novel sequential design strategy for global surrogate modeling

  2009influential reference
• Optimizing Latin hypercube design for sequential sampling of computer experiments

  2009cited by this paper
• Finding maximin latin hypercube designs by Iterated Local Search heuristics

  2009cited by this paper
• ORTHOGONAL-MAXIMIN LATIN HYPERCUBE DESIGNS

  2008cited by this paper
• Hierarchical Nonlinear Approximation for Experimental Design and Statistical Data Fitting

  2007cited by this paper
• Towards a Black Box Algorithm for Nonlinear Function Approximation over High-Dimensional Domains

  2007cited by this paper
• Maximin Latin Hypercube Designs in Two Dimensions

  2007influential reference
• Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error

  2006cited by this paper
• Statistics for Experimenters: Design, Innovation, and Discovery

  2006cited by this paper
• Statistics for Experimenters: Design, Innovation and Discovery

  2006cited by this paper
• Adaptive Distributed Metamodeling

  2006cited by this paper
• Maximin designs for computer experiments

  2006influential reference
• Could enough samples be more important than better designs for computer experiments?

  2005cited by this paper
• An Efficient Algorithm for Constructing Optimal Design of Computer Experiments

  2005cited by this paper
• The Design and Analysis of Computer Experiments

  2003cited by this paper
• Small response surface designs for metamodel estimation

  2003cited by this paper
• High Performance Computing for Computational Science

  2003cited by this paper
• Ch. 4. Uniform experimental designs and their applications in industry

  2003cited by this paper
• On Sequential Sampling for Global Metamodeling in Engineering Design

  2002cited by this paper
• Adaptive sampling applied to multivariate, multiple output rational interpolation models with application to microwave circuits

  2002cited by this paper
• Centered L2-discrepancy of random sampling and Latin hypercube design, and construction of uniform designs

  2002cited by this paper
• Metamodels for Computer-based Engineering Design: Survey and recommendations

  2001cited by this paper
• Design and Analysis of Experiments

  2001cited by this paper
• Algorithmic construction of optimal symmetric Latin hypercube designs

  2000cited by this paper
• A generalized discrepancy and quadrature error bound

  1998cited by this paper
• Design and analysis of computer experiments

  1998cited by this paper
• Exploratory designs for computational experiments

  1995cited by this paper
• Orthogonal Array-Based Latin Hypercubes

  1993cited by this paper
• Random number generation and Quasi-Monte Carlo methods

  1992cited by this paper
• Minimax and maximin distance designs

  1990cited by this paper

• A novel adaptive sampling approach with batch selection for the automatic generation of surrogate models in geotechnical engineering

  2026cites this paper
• Meta-learning Gaussian processes for engineering surrogate modeling with cross-validation- and variance-guided adaptive sampling

  2026cites this paper
• A simple parallel surrogate optimization method over mixed design spaces/dsopt

  2026cites this paper
• A Process Systems Engineering Framework for Adaptive Sample Size Determination in AutoML Pipelines

  2026cites this paper
• overhang_surrogates: A Python package for sampling, training and visualising surrogate models for building energy simulations

  2026cites this paper
• Effect of occupant and restraint variability in reclined positions on submarining probability in frontal car crash scenarios

  2025cites this paper
• Parallel Monte Carlo-based surrogate optimization of building energy models

  2025cites this paper
• Cluster-based adaptive sampling methodology for systems modeling

  2025cites this paper
• "LHS in LHS": A new expansion strategy for Latin hypercube sampling in simulation design

  2025cites this paper
• A pointwise weighted hybrid surrogate model based on hybrid measures for engineering optimization

  2025cites this paper
• Explainable AI Framework for Deep Learning-based Network Digital Twins

  2025cites this paper
• Aerodynamic Optimization Design of Tandem-Wing Configurations Based on Multi-Fidelity Deep Neural Networks

  2025cites this paper
• Nested Latin Hypercube-Based Sampling for Efficient Uncertainty Quantification Using Sensitivity-Assisted Least Squares SVM

  2025cites this paper
• Physics-informed machine learning surrogate for scalable simulation of thermal histories during wire-arc directed energy deposition

  2025cites this paper
• Leveraging Machine Learning hybrid framework and Multi-Objective Optimization for Efficient Catalytic carbon dioxide Hydrogenation to Methanol

  2025cites this paper
• Predicting mechanical properties of elastomer honeycombs using fast image-based measurements

  2025cites this paper
• Efficient Methods for Achieving Data Coverage in Machine Learning Assurance

  2025cites this paper
• Design of radiation tolerant SiC MOSFET power devices with multi-fidelity surrogate model

  2025cites this paper
• URBaM: A Novel Surrogate Modelling Method to Determine Design Scaling Rules for Product Families

  2025cites this paper
• Progressive DNN-metaheuristics for programmable broadband mechanical metamaterial absorbers design

  2025cites this paper
• A Review on Data-Driven Constitutive Laws for Solids

  2024cites this paper
• Posterior sampling with Adaptive Gaussian Processes in Bayesian parameter identification

  2024influential citation
• Coverage-Driven Synthetic Data Generation for Machine Learning Assurance

  2024cites this paper
• Adaptive Gradient Enhanced Gaussian Process Surrogates for Inverse Problems

  2024cites this paper
• Research on improving parallel sequence sampling method in ship type optimization

  2024cites this paper
• Deep neural network-based modeling and optimization methodology of fuel cell electric vehicles considering power sources and electric motors

  2024cites this paper
• A Novel Electromagnetic Environment Measurement System

  2024cites this paper
• A computationally efficient approach of tuned mass damper design for a nuclear cabinet based on two-step machine learning and optimization methods

  2024cites this paper
• An uncertainty-based objective function for hyperparameter optimization in Gaussian processes applied to expensive black-box problems

  2024cites this paper
• An experimental design-based approach for modelling of weapon engagement zone of an air-to-air missile

  2024influential citation
• Energy loss and efficiency investigations of a dual clutch transmission based on adaptive experiment and analytical simulation

  2024cites this paper
• Adaptive Gaussian Process Regression for Bayesian inverse problems

  2024cites this paper
• Comparison of ANN and XGBoost surrogate models trained on small numbers of building energy simulations

  2024influential citation
• Sampling-based test scenarios searching method for autonomous system robustness evaluation

  2024cites this paper
• Data-Driven Production Planning Formulations with Inventory Considerations

  2023cites this paper
• Dimensionality-reduced antenna modeling with stochastically established constrained domain

  2023cites this paper
• Effect of adaptive intelligent sampling and machine-learning emulators in surrogate energy modeling of architectural massing

  2023cites this paper
• A Multi-Fidelity Successive Response Surface Method for Crashworthiness Optimization Problems

  2023cites this paper
• Reduced-cost microwave modeling using constrained domains and dimensionality reduction

  2023cites this paper
• Adaptive Latin Hypercube Sampling for a Surrogate-Based Optimization with Artificial Neural Network

  2023cites this paper
• Propagating input uncertainties into parameter uncertainties and model prediction uncertainties—A review

  2023cites this paper
• Data-Driven Production Planning Models for Wafer Fabs: An Exploratory Study

  2023cites this paper
• An adaptive sequential sampling method based on ANN_MCD and RF: Application in geotechnical problems

  2023cites this paper
• HPOSS: A hierarchical portfolio optimization stacking strategy to reduce the generalization error of ensembles of models

  2023cites this paper
• Receding Horizon Cost-Aware Adaptive Sampling for Environmental Monitoring

  2023cites this paper
• Application of an improved maximum entropy sampling method in hull form optimization

  2023cites this paper
• Fast adaptive sampling with operation time control

  2023cites this paper
• Adaptive Gaussian process regression for efficient building of surrogate models in inverse problems

  2023cites this paper
• Hybrid Particle Swarm Optimization for High-Dimensional Latin Hypercube Design Problem

  2023cites this paper
• Efficient Adaptive Monte Carlo Uncertainty Forecasting for High Dimensional Nonlinear Dynamic Systems

  2023influential citation
• Geometric design of micro scale volumetric receiver using system-level inputs: An application of surrogate-based approach

  2022cites this paper
• HOMOGENEOUS PLANS OF MULTI-FACTORY EXPERIMENTS ON QUASI-RANDOM R-ROBERTS SEQUENCES FOR SURROGATE MODELING IN A VORTEX STYLE STRUCTUROSCOPY

  2022cites this paper
• Efficiency of uncertainty propagation methods for moment estimation of uncertain model outputs

  2022cites this paper
• Designing higher value roads to preserve species at risk by optimally controlling traffic flow

  2022influential citation
• Model Predictivity Assessment: Incremental Test-Set Selection and Accuracy Evaluation

  2022cites this paper
• Recent advances and applications of surrogate models for finite element method computations: a review

  2022cites this paper
• Combining Numerical Simulations, Artificial Intelligence and Intelligent Sampling Algorithms to Build Surrogate Models and Calculate the Probability of Failure of Urban Tunnels

  2022cites this paper
• Isovolumetric adaptations to space-filling design of experiments

  2022cites this paper
• Efficient Sampling Algorithm for Electric Machine Design Calculations incorporating Empirical Knowledge

  2022cites this paper
• Non destructive Eddy Currents inversion using Artificial Neural Networks and data augmentation

  2022cites this paper
• Exploration-oriented sampling strategies for global surrogate modeling: A comparison between one-stage and adaptive methods

  2022cites this paper
• Space–Time Adaptive Modeling and Shape Optimization of Microwave Structures With Applications to Metasurface Design

  2022cites this paper
• A Computationally Efficient Surrogate Model Based Robust Optimization for Permanent Magnet Synchronous Machines

  2022cites this paper
• An active-learning probabilistic neural network for feasibility classification of constrained engineering optimization problems

  2021cites this paper
• Optimization with Constraint Learning: A Framework and Survey

  2021cites this paper
• Introducing Metamodel-Based Global Calibration of Material-Specific Simulation Parameters for Discrete Element Method

  2021cites this paper
• Linking the modulation of gear mesh vibration in planetary gearboxes to manufacturing deviations

  2021cites this paper
• Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation

  2021cites this paper
• A Stepwise Optimal Design Applied to an Interior Permanent Magnet Synchronous Motor for Electric Vehicle Traction Applications

  2021cites this paper
• An active learning method combining adaptive kriging and weighted penalty for structural reliability analysis

  2021cites this paper
• Failure identification in a nuclear passive safety system by Monte Carlo simulation with adaptive Kriging

  2021cites this paper
• Adaptive Sampling for Global Meta Modeling Using a Gaussian Process Variance Measure

  2021cites this paper
• Greedy maximin distance sampling based model order reduction of prestressed and parametrized abdominal aortic aneurysms

  2021cites this paper
• Flaw characterization in conductive media based on pulsed Eddy current measurements: A fast non‐iterative inversion approach

  2021cites this paper
• Comparative Case Study of a Metamodel-Based Electric Vehicle Powertrain Design

  2021cites this paper
• Analyzing randomness effects on the reliability of exploratory landscape analysis

  2021cites this paper
• Intelligent sampling for surrogate modeling, hyperparameter optimization, and data analysis

  2021influential citation
• Integrating Process‐Based Reactive Transport Modeling and Machine Learning for Electrokinetic Remediation of Contaminated Groundwater

  2021cites this paper
• A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design

  2021cites this paper
• Development of surrogate models in reliability-based design optimization: A review.

  2021cites this paper
• Constrained space-filling and non-collapsing sequential design of experiments and its application for the lightweight design of cylindrical stiffened shells

  2021cites this paper
• Progressive design of gradually stiffer metamaterial using surrogate model

  2021cites this paper
• Bayesian optimization for a multiple-component system with target values

  2021cites this paper
• A unified ensemble of surrogates with global and local measures for global metamodelling

  2020cites this paper
• On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics

  2020cites this paper
• An Efficient Batch K-Fold Cross-Validation Voronoi Adaptive Sampling Technique for Global Surrogate Modeling

  2020cites this paper
• Introduction to Metamodeling for Reducing Computational Burden of Advanced Analyses with Health Economic Models: A Structured Overview of Metamodeling Methods in a 6-Step Application Process

  2020cites this paper
• Basics of Data-Driven Surrogate Modeling

  2020cites this paper
• Analysis of an individual‐based influenza epidemic model using random forest metamodels and adaptive sequential sampling

  2020cites this paper
• VISCOUS: A Variance‐Based Sensitivity Analysis Using Copulas for Efficient Identification of Dominant Hydrological Processes

  2020cites this paper
• Modulation der Zahneingriffsschwingungen von Planetengetrieben

  2020cites this paper
• Robust Design Optimization of Surface-Mounted Permanent Magnet Synchronous Motor Using Uncertainty Characterization by Bootstrap Method

  2020cites this paper
• An enhanced Kriging surrogate modeling technique for high-dimensional problems

  2020cites this paper
• Reliable Surrogate Modeling of Antenna Input Characteristics by Means of Domain Confinement and Principal Components

  2020cites this paper
• Versatile sequential sampling algorithm using Kernel Density Estimation

  2020cites this paper
• Design-Oriented Modeling of High-Frequency Structures

  2020cites this paper
• Surrogate Model Based Analysis of Inter-Ply Shear Stress in Fiber Reinforced Thermoplastic Composite Sheet Press Forming

  2020cites this paper
• Interval optimization for structural dynamic responses of an artillery system under uncertainty

  2020cites this paper
• State-of-the-Art and Comparative Review of Adaptive Sampling Methods for Kriging

  2020cites this paper
• Uncertainty identification method using kriging surrogate model and Akaike information criterion for industrial electromagnetic device

  2020cites this paper