A development environment for robust and global optimization
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Updated
Mar 8, 2024 - Julia
A development environment for robust and global optimization
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
Data-driven decision making under uncertainty using matrices
Introductory (adjustable) robust optimization by matrix computation with box uncertainty and budget of uncertainty.
Reliability based design optimization of a non-linear controller
Distributionally Robust Graphical Models
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