Global and preference-based optimization with mixed variables using piecewise affine surrogates
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Publication:6667570
DOI10.1007/s10957-024-02596-yMaRDI QIDQ6667570
Publication date: 20 January 2025
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
derivative-free optimizationmixed-integer linear programmingsurrogate modelspreference-based optimization
Cites Work
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- A literature survey of benchmark functions for global optimisation problems
- An adaptive radial basis algorithm (ARBF) for expensive black-box global optimization
- Efficient global optimization of expensive black-box functions
- RBFOpt: an open-source library for black-box optimization with costly function evaluations
- Optimizing radial basis functions by d.c. programming and its use in direct search for global derivative-free optimization
- Mixed logical-linear programming
- Global optimization via inverse distance weighting and radial basis functions
- Global optimization based on active preference learning with radial basis functions
- Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques
- MISO: mixed-integer surrogate optimization framework
- A general mathematical framework for constrained mixed-variable blackbox optimization problems with meta and categorical variables
- A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
- Testing Unconstrained Optimization Software
- Derivative-Free and Blackbox Optimization
- Least squares quantization in PCM
- The Nonstochastic Multiarmed Bandit Problem
- Mixed-Integer Convex Nonlinear Optimization with Gradient-Boosted Trees Embedded
- Benchmarking Derivative-Free Optimization Algorithms
- Algorithm 1027: NOMAD Version 4: Nonlinear Optimization with the MADS Algorithm
- Introduction to global optimization.
- Random forests
- A Piecewise Linear Regression and Classification Algorithm With Application to Learning and Model Predictive Control of Hybrid Systems
- A taxonomy of constraints in black-box simulation-based optimization
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