Efficient Global Optimization of Expensive Black-Box Functions
Cited by (1,004)
Items 201–300 of 1,004
- A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity PatternsChun‐Ren Phang, Fuad M. Noman, Hadri Hussain, Chee‐Ming Ting, Hernando Ombao · 2019 · IEEE Journal of Biomedical and Health Informatics
- Modeling, Simulation, and Optimization of Postcombustion CO 2 Capture for Variable Feed Concentration and Flow Rate. 2. Pressure Swing Adsorption and Vacuum Swing Adsorption ProcessesM. M. Faruque Hasan, Richard C. Baliban, Josephine A. Elia, Christodoulos A. Floudas · 2012 · Industrial & Engineering Chemistry Research
- Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyondArun Mannodi‐Kanakkithodi, Anand R. Chandrasekaran, Chiho Kim, Tran Doan Huan, Ghanshyam Pilania, Venkatesh Botu, Rampi Ramprasad · 2017 · Materials Today
- Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global OptimizationJanet, Jon Paul, Ramesh, Sahasrajit, Duan, Chenru, Kulik, Heather J. · 2020 · ACS Central Science
- Multiobjective Infill Criterion Driven Gaussian Process-Assisted Particle Swarm Optimization of High-Dimensional Expensive ProblemsJie Tian, Ying Tan, Jianchao Zeng, Chaoli Sun, Yaochu Jin · 2018 · IEEE Transactions on Evolutionary Computation
- A systematic comparison of metamodeling techniques for simulation optimization in Decision Support SystemsYan‐Fu Li, Szu Hui Ng, Min Xie, T.N. Goh · 2009 · Applied Soft Computing
- Machine learning in materials design and discovery: Examples from the present and suggestions for the futureJames E. Gubernatis, Turab Lookman · 2018 · Physical Review Materials
- SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problemsJuliane Müller, Christine A. Shoemaker, Robert Piché · 2012 · Computers & Operations Research
- Optimization using surrogate models and partially converged computational fluid dynamics simulationsAlexander I. J. Forrester, Neil W. Bressloff, Andy J. Keane · 2006 · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
- A review of the recent progress in battery informaticsChen Ling · 2022 · npj Computational Materials
- SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter OptimizationLindauer, Marius, Eggensperger, Katharina, Feurer, Matthias, Biedenkapp, André, Deng, Difan, Benjamins, Carolin, Ruhopf, Tim, Sass, René, Hutter, Frank · 2021 · arXiv
- Infill sampling criteria for surrogate-based optimization with constraint handlingJim Parr, Andy J. Keane, Alexander I. J. Forrester, Carren M. E. Holden · 2012 · Engineering Optimization
- Simulation Optimization: A Review and Exploration in the New Era of Cloud Computing and Big DataJie Xu, Edward Huang, Chun‐Hung Chen, Loo Hay Lee · 2015 · Asia Pacific Journal of Operational Research
- A Novel Evolutionary Sampling Assisted Optimization Method for High-Dimensional Expensive ProblemsXinjing Wang, G. Gary Wang, Baowei Song, Peng Wang, Yang Wang · 2019 · IEEE Transactions on Evolutionary Computation
- Materials informatics: From the atomic-level to the continuumJeffrey M. Rickman, Turab Lookman, Sergei V. Kalinin · 2019 · Acta Materialia
- Distributed Gaussian ProcessesMarc Peter Deisenroth, Ng, JW · 2015 · arXiv (Cornell University)
- Interval model updating with irreducible uncertainty using the Kriging predictorHamed Haddad Khodaparast, John E. Mottershead, Kenneth Badcock · 2010 · Mechanical Systems and Signal Processing
- Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimationMichael Eldred, Laura Painton Swiler, G. Tang · 2011 · Reliability Engineering & System Safety
- Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and ChallengesGuang Chen, Zhiqiang Shen, Akshay Iyer, Umar Farooq Ghumman, Shan Tang, Jinbo Bi, Wei Chen, Ying Li · 2020 · Polymers
- Bayesian Optimization for Accelerating Hyper-Parameter TuningVu Nguyen · 2019 · IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
- Data‐Driven Materials Innovation and ApplicationsZhuo Wang, Zhehao Sun, Hang Yin, Xinghui Liu, Jinlan Wang, Haitao Zhao, Cheng Heng Pang, Tao Wu, Shuzhou Li, Zongyou Yin et al. · 2022 · Advanced Materials
- A derivative-free methodology with local and global search for the constrained joint optimization of well locations and controlsObiajulu J. Isebor, Louis J. Durlofsky, David Echeverría Ciaurri · 2013 · Computational Geosciences
- A Sequential Kriging reliability analysis method with characteristics of adaptive sampling regions and parallelizabilityZhixun Wen, Haiqing Pei, Hai Liu, Zhufeng Yue · 2016 · Reliability Engineering & System Safety
- Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manualSandia National Laboratories (SNL), Albuquerque, NM (United States). New Mexico Small Business Assistance (NMSBA) Program, NM (United States), Brian Adams, USDOE National Nuclear Security Administration (NNSA), Mohamed Ebeida, Michael Eldred, John Jakeman, Laura Swiler, John Stephens, Dena M. Vigil, Timothy Michael Wildey et al. · 2014
- Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary ComputationBernd Bischl, Olaf Mersmann, Heike Trautmann, Claus Weihs · 2012 · Evolutionary Computation
- Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagationRohit K. Tripathy, Ilias Bilionis, Marcial Gonzalez · 2016 · Journal of Computational Physics
- A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian OptimizationMickaël Binois, Nathan Wycoff · 2022 · ACM Transactions on Evolutionary Learning and Optimization
- Quantile-Based Optimization of Noisy Computer Experiments With Tunable PrecisionVictor Picheny, David Ginsbourger, Yann Richet, Grégory Caplin · 2012 · Technometrics
- Convergence properties of the expected improvement algorithm with fixed mean and covariance functionsEmmanuel Vázquez, Julien Bect · 2010 · Journal of Statistical Planning and Inference
- Global optimization of metasurface designs using statistical learning methodsMahmoud M. R. Elsawy, Stéphane Lanteri, Régis Duvigneau, Gauthier Brière, Mohamed Sabry Mohamed, Patrice Genevet · 2019 · Scientific Reports
- Sequential Approximate Optimization using Radial Basis Function network for engineering optimizationSatoshi KITAYAMA, Masao Arakawa, Koetsu YAMAZAKI · 2010 · Optimization and Engineering
- Maximin Latin Hypercube Designs in Two DimensionsEdwin van Dam, B.G.M. Husslage, Dick den Hertog, J.B.M. Melissen · 2007 · Operations Research
- Surrogate‐based methods for black‐box optimizationKy Vu, Claudia D’Ambrosio, Youssef Hamadi, Leo Liberti · 2016 · International Transactions in Operational Research
- Stochastic radial basis function algorithms for large-scale optimization involving expensive black-box objective and constraint functionsRommel G. Regis · 2010 · Computers & Operations Research
- Model-based methods for continuous and discrete global optimizationThomas Bartz–Beielstein, Martin Zaefferer · 2017 · Applied Soft Computing
- Efficient aerodynamic shape optimization using variable-fidelity surrogate models and multilevel computational gridsZhonghua Han, Chenzhou Xu, Liang Zhang, Yu Zhang, Keshi ZHANG, Wenping Song · 2019 · Chinese Journal of Aeronautics
- Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-studyGustavo A. Lujan-Moreno, Phillip Howard, Omar Rojas, Douglas C. Montgomery · 2018 · Expert Systems with Applications
- Weighted Gradient-Enhanced Kriging for High-Dimensional Surrogate Modeling and Design OptimizationZhonghua Han, Yu Zhang, Chenxing Song, Ke‐Shi Zhang · 2017 · AIAA Journal
- Multi-objective Optimization for Materials Discovery via Adaptive DesignAbhijith Gopakumar, Prasanna V. Balachandran, Dezhen Xue, James E. Gubernatis, Turab Lookman · 2018 · Scientific Reports
- RBFOpt: an open-source library for black-box optimization with costly function evaluationsAlberto Costa, Giacomo Nannicini · 2018 · Mathematical Programming Computation
- G ryffin : An algorithm for Bayesian optimization of categorical variables informed by expert knowledgeFlorian Häse, Matteo Aldeghi, Riley J. Hickman, Loïc M. Roch, Alán Aspuru‐Guzik · 2021 · Applied Physics Reviews
- High-dimensional Bayesian optimization using low-dimensional feature spacesRiccardo Moriconi, Marc Peter Deisenroth, K.S. Kumar · 2020 · Machine Learning
- Airfoil Design Parameterization and Optimization Using Bézier Generative Adversarial NetworksWei Chen, Kevin N. Chiu, Mark Fuge · 2020 · AIAA Journal
- Multi-fidelity modelling via recursive co-kriging and Gaussian–Markov random fieldsParis G. Perdikaris, Daniele Venturi, Johannes Ø. Røyset, George Em Karniadakis · 2015 · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
- A Surrogate-Assisted Multiswarm Optimization Algorithm for High-Dimensional Computationally Expensive ProblemsFan Li, Xiwen Cai, Liang Gao, Weiming Shen · 2020 · IEEE Transactions on Cybernetics
- Efficient Aerodynamic Shape Optimization with Deep-Learning-Based Geometric FilteringJichao Li, Mengqi Zhang, Joaquim R. R. A. Martins, Chang Shu · 2020 · AIAA Journal
- Efficient Generalized Surrogate-Assisted Evolutionary Algorithm for High-Dimensional Expensive ProblemsXiwen Cai, Liang Gao, Xinyu Li · 2019 · IEEE Transactions on Evolutionary Computation
- Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial pointsRommel G. Regis · 2013 · Engineering Optimization
- Machine Learning into MetaheuristicsEl‐Ghazali Talbi · 2021 · ACM Computing Surveys
- ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFsZheng, Zhiling, Zhang, Oufan, Nguyen, Ha L., Rampal, Nakul, Alawadhi, Ali H., Rong, Zichao, Head-Gordon, Teresa, Borgs, Christian, Chayes, Jennifer T., Yaghi, Omar M. · 2023 · ACS Central Science
- Boosting Data-Driven Evolutionary Algorithm With Localized Data GenerationJian-Yu Li, Zhi‐Hui Zhan, Chuan Xi Wang, Hu Jin, Jun Zhang · 2020 · IEEE Transactions on Evolutionary Computation
- Efficient aerodynamic shape optimization of transonic wings using a parallel infilling strategy and surrogate modelsJing Liu, Wen Ping Song, Zhonghua Han, Yan Zhang · 2016 · Structural and Multidisciplinary Optimization
- An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimizationXilu Wang, Yaochu Jin, Sebastian Schmitt, Markus Olhofer · 2020 · Information Sciences
- Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for computationally expensive black-box global optimization problemsJuliane Müller, Christine A. Shoemaker · 2014 · Journal of Global Optimization
- laGP : Large-Scale Spatial Modeling via Local Approximate Gaussian Processes in RRobert B. Gramacy · 2016 · Journal of Statistical Software
- Crystal structure prediction accelerated by Bayesian optimizationTomoki Yamashita, Nobuya Sato, Hiori Kino, Takashi Miyake, Koji Tsuda, Tamio Oguchi · 2018 · Physical Review Materials
- REAK: Reliability analysis through Error rate-based Adaptive KrigingZeyu Wang, Abdollah Shafieezadeh · 2018 · Reliability Engineering & System Safety
- Recent applications of machine learning in alloy design: A reviewMingwei Hu, Qiyang Tan, Ruth Knibbe, Miao Xu, Bin Jiang, Sen Wang, Xue Li, Mingxing Zhang · 2023 · Materials Science and Engineering R Reports
- Hybrid Variable Fidelity Optimization by Using a Kriging-Based Scaling FunctionShawn Gano, John E. Renaud, Brian Sanders · 2005 · AIAA Journal
- Lightweight design of automotive composite bumper system using modified particle swarm optimizerZhao Liu, Jiahai Lu, Ping Zhu · 2016 · Composite Structures
- Bayesian truncation errors in chiral effective field theory: Nucleon-nucleon observablesJ. A. Melendez, Sarah Wesolowski, R. J. Furnstahl · 2017 · Physical Review C
- Predictive Entropy Search for Efficient Global Optimization of Black-box FunctionsJosé Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani A · 2014 · arXiv (Cornell University)
- Update strategies for kriging models used in variable fidelity optimizationShawn Gano, John E. Renaud, Jay D. Martin, Timothy W. Simpson · 2006 · Structural and Multidisciplinary Optimization
- Portfolio allocation for Bayesian optimizationMatthew D. Hoffman, Eric Brochu, Nando de Freitas · 2011
- Toward autonomous design and synthesis of novel inorganic materialsNathan J. Szymanski, Yan Zeng, Haoyan Huo, Christopher J. Bartel, Haegyeom Kim, Gerbrand Ceder · 2021 · Materials Horizons
- Education Policy and Intergenerational Transfers in EquilibriumBrant Abbott, Giovanni Gallipoli, Costas Meghir, Giovanni L. Violante · 2018 · Journal of Political Economy
- A Simple Approach to Emulation for Computer Models With Qualitative and Quantitative FactorsQiang Zhou, Peter Z. G. Qian, Shiyu Zhou · 2011 · Technometrics
- Global Optimization of Costly Nonconvex Functions Using Radial Basis FunctionsMattias Björkman, Kenneth Holmström · 2000 · Optimization and Engineering
- High Dimensional Bayesian Optimisation and Bandits via Additive ModelsKirthevasan Kandasamy, Jeff Schneider, Barnabás Póczos · 2015 · arXiv (Cornell University)
- Data-driven de novo design of super-adhesive hydrogelsLiao, Hongguang, Hu, Sheng, Yang, Hu, Wang, Lei, Tanaka, Shinya, Takigawa, Ichigaku, Li, Wei, Fan, Hailong, Gong, Jian Ping · 2025 · Nature
- Understanding the Effects of Model Uncertainty in Robust Design With Computer ExperimentsDaniel W. Apley, Jun Liu, Wei Chen · 2005 · Journal of Mechanical Design
- Simulation optimization: a review of algorithms and applicationsSatyajith Amaran, Nikolaos V. Sahinidis, Bikram Sharda, Scott J. Bury · 2014 · 4OR
- An adaptive hybrid surrogate modelJie Zhang, Souma Chowdhury, Achille Messac · 2012 · Structural and Multidisciplinary Optimization
- Perspectives on the continuous manufacturing of powder‐based pharmaceutical processesMarianthi Ierapetritou, Fernando J. Muzzio, Gintaras V. Reklaitis · 2016 · AIChE Journal
- Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradientKaifeng Yang, Michael Emmerich, Andre H. Deutz, Thomas Bäck · 2018 · Swarm and Evolutionary Computation
- Local Function Approximation in Evolutionary Algorithms for the Optimization of Costly FunctionsRommel G. Regis, Christine A. Shoemaker · 2004 · IEEE Transactions on Evolutionary Computation
- Thermal load forecasting in district heating networks using deep learning and advanced feature selection methodsSuryanarayana, Gowri, Lago, Jesus, Geysen, Davy, Aleksiejuk, Piotr, Johansson, Christian · 2018 · Energy
- Multiproblem Surrogates: Transfer Evolutionary Multiobjective Optimization of Computationally Expensive ProblemsAlan Tan Wei Min, Yew-Soon Ong, Abhishek Gupta, Chi-Keong Goh · 2017 · IEEE Transactions on Evolutionary Computation
- Toward Machine Learning-Enhanced High-Throughput ExperimentationNatalie S. Eyke, Brent A. Koscher, Klavs F. Jensen · 2021 · Trends in Chemistry
- Wing Optimization Using Design of Experiment, Response Surface, and Data Fusion MethodsAndy J. Keane · 2003 · Journal of Aircraft
- ReLU networks as surrogate models in mixed-integer linear programsBjarne Grimstad, Henrik Andersson · 2019 · Computers & Chemical Engineering
- A review of machine learning methods applied to structural dynamics and vibroacousticBarbara Zaparoli Cunha, Christophe Droz, Abdelmalek Zine, Stéphane Foulard, Mohamed Najib Ichchou · 2023 · Mechanical Systems and Signal Processing
- Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data PoisoningCinà, Antonio Emanuele, Grosse, Kathrin, Demontis, Ambra, Vascon, Sebastiano, Zellinger, Werner, Moser, Bernhard A., Oprea, Alina, Biggio, Battista, Pelillo, Marcello, Roli, Fabio · 2023 · ACM Computing Surveys
- Surrogate-Based OptimizationZhonghua Han, Ke‐Shi Zhang · 2012 · InTech eBooks
- Adaptive kriging-based efficient reliability method for structural systems with multiple failure modes and mixed variablesNing‐Cong Xiao, Kai Yuan, Chengning Zhou · 2019 · Computer Methods in Applied Mechanics and Engineering
- Automated machine learning: past, present and futureMitra Baratchi, Can Wang, Steffen Limmer, Jan N. van Rijn, Holger H. Hoos, Thomas Bäck, Markus Olhofer · 2024 · Artificial Intelligence Review
- A Bayesian approach to constrained single- and multi-objective optimizationPaul Feliot, Julien Bect, Emmanuel Vázquez · 2016 · Journal of Global Optimization
- Gradient-enhanced kriging for high-dimensional problemsMohamed Amine Bouhlel, Joaquim R. R. A. Martins · 2018 · Engineering With Computers
- A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantificationSeongok Ryu, Yongchan Kwon, Woo Youn Kim · 2019 · Chemical Science
- AKOIS: An adaptive Kriging oriented importance sampling method for structural system reliability analysisXufang Zhang, Lei Wang, John Dalsgaard Sørensen · 2019 · Structural Safety
- Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a reviewJunhyeong Lee, Donggeun Park, Mingyu Lee, Hugon Lee, Kundo Park, Ikjin Lee, Seunghwa Ryu · 2023 · Materials Horizons
- Improved Strategies for Radial basis Function Methods for Global OptimizationRommel G. Regis, Christine A. Shoemaker · 2006 · Journal of Global Optimization
- Constrained efficient global optimization with support vector machinesAnirban Basudhar, Christoph Dribusch, Sylvain Lacaze, Samy Missoum · 2012 · Structural and Multidisciplinary Optimization
- Uncertainty quantification and management in additive manufacturing: current status, needs, and opportunitiesZhen Yu Hu, Sankaran Mahadevan · 2017 · The International Journal of Advanced Manufacturing Technology
- Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selectionTaimoor Akhtar, Christine A. Shoemaker · 2015 · Journal of Global Optimization
- A Maximum Confidence Enhancement Based Sequential Sampling Scheme for Simulation-Based DesignZequn Wang, Pingfeng Wang · 2013 · Journal of Mechanical Design
- Bayesian optimization for sensor set selectionRoman Garnett, Michael A. Osborne, Stephen Roberts · 2010 · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
- Multiobjective Evolutionary Algorithms in Aeronautical and Aerospace EngineeringAlfredo Arias-Montaño, Carlos A. Coello Coello, Efrén Mezura‐Montes · 2012 · IEEE Transactions on Evolutionary Computation
- Adaptive and Resilient Soft Tensegrity RobotsJohn A. Rieffel, Jean-Baptiste Mouret · 2018 · Soft Robotics
- Multiple Classifiers-Assisted Evolutionary Algorithm Based on Decomposition for High-Dimensional Multiobjective ProblemsTakumi Sonoda, Masaya Nakata · 2022 · IEEE Transactions on Evolutionary Computation