SMGO-Δ: Balancing caution and reward in global optimization with black-box constraints
出版年份 2022 全文链接
标题
SMGO-Δ: Balancing caution and reward in global optimization with black-box constraints
作者
关键词
-
出版物
INFORMATION SCIENCES
Volume 605, Issue -, Pages 15-42
出版商
Elsevier BV
发表日期
2022-05-07
DOI
10.1016/j.ins.2022.05.017
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- An Efficient Constrained Global Optimization Algorithm with a Clustering-Assisted Multiobjective Infill Criterion Using Gaussian Process Regression for Expensive Problems
- (2021) Puyu Jiang et al. INFORMATION SCIENCES
- Two decades of blackbox optimization applications
- (2021) Stéphane Alarie et al. EURO Journal on Computational Optimization
- SMGO: A set membership approach to data-driven global optimization
- (2021) Lorenzo Sabug et al. AUTOMATICA
- Surrogate-based optimisation using adaptively scaled radial basis functions
- (2020) Magnus Urquhart et al. APPLIED SOFT COMPUTING
- Design of IMEXRK time integration schemes via Delaunay-based derivative-free optimization with nonconvex constraints and grid-based acceleration
- (2020) Ryan Alimo et al. JOURNAL OF GLOBAL OPTIMIZATION
- Delaunay-based derivative-free optimization via global surrogates. Part III: nonconvex constraints
- (2020) Ryan Alimo et al. JOURNAL OF GLOBAL OPTIMIZATION
- Global optimization via inverse distance weighting and radial basis functions
- (2020) Alberto Bemporad COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
- Expected improvement for expensive optimization: a review
- (2020) Dawei Zhan et al. JOURNAL OF GLOBAL OPTIMIZATION
- Kriging-assisted Teaching-Learning-based Optimization (KTLBO) to Solve Computationally Expensive Constrained Problems
- (2020) Huachao Dong et al. INFORMATION SCIENCES
- Filter-based adaptive kriging method for black-box optimization problems with expensive objective and constraints
- (2019) Renhe Shi et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints
- (2019) Eduardo C. Garrido-Merchán et al. NEUROCOMPUTING
- A feasible-ratio control technique for constrained optimization
- (2019) Ruwang Jiao et al. INFORMATION SCIENCES
- Sequential model based optimization of partially defined functions under unknown constraints
- (2019) Candelieri Antonio JOURNAL OF GLOBAL OPTIMIZATION
- A peak-over-threshold search method for global optimization
- (2018) Siyang Gao et al. AUTOMATICA
- A hybrid GSA-GA algorithm for constrained optimization problems
- (2018) Harish Garg INFORMATION SCIENCES
- Implementation of Cartesian grids to accelerate Delaunay-based derivative-free optimization
- (2017) Pooriya Beyhaghi et al. JOURNAL OF GLOBAL OPTIMIZATION
- Learning a Nonlinear Controller From Data: Theory, Computation, and Experimental Results
- (2016) Lorenzo Fagiano et al. IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- A Kriging-based constrained global optimization algorithm for expensive black-box functions with infeasible initial points
- (2016) Yaohui Li et al. JOURNAL OF GLOBAL OPTIMIZATION
- Taking the Human Out of the Loop: A Review of Bayesian Optimization
- (2016) Bobak Shahriari et al. PROCEEDINGS OF THE IEEE
- Kriging-based infill sampling criterion for constraint handling in multi-objective optimization
- (2015) Jesús Martínez-Frutos et al. JOURNAL OF GLOBAL OPTIMIZATION
- Derivative-free optimization for expensive constrained problems using a novel expected improvement objective function
- (2014) Fani Boukouvala et al. AICHE JOURNAL
- Multidimensional global extremum seeking via the DIRECT optimisation algorithm
- (2013) Sei Zhen Khong et al. AUTOMATICA
- Algorithm 909
- (2011) Sébastien Le Digabel ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
- An efficient multi-objective optimization method for black-box functions using sequential approximate technique
- (2011) Guodong Chen et al. APPLIED SOFT COMPUTING
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