Implementations of optimization techniques, sampling methods and evolutionary algorithms
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Updated
Jan 3, 2024 - Jupyter Notebook
Implementations of optimization techniques, sampling methods and evolutionary algorithms
Multivariable Numerical Optimization
Optimising HSD components (e.g. LVDS, ECL, CML) parameters using Bayesian Optimisation
Implementation of various Bayesian Optimization algorithms
Multivariable control strategy for a reactor system, efficient global solution method for a reaction system and rocket, solution methods for two approximate formulations of the Bayesian optimal experiment design (OED) problem, optimal control approach for a cold plasma system.
Here we visualize the need for robust BO against an adversary. Clearly the optimum design point changes depending the uncertain parameter x, so we should identify a region for which the decision variable x resides in an optimal region.
Safe Explorative Bayesian Optimization -- Towards Personalized Treatments in Plasma Medicine
Object-Orientated Derivative-Free Optimisation
Derivative-free solver for the minimization of a function over the convex hull of a set of vectors
Code for Dividing Rectangles Attack Multi-Objective Optimization
Black-box optimization for real-world scenario
This code obtains closed-loop performance guarantees for automated controller tuning, which can be formulated as a black-box optimization problem under uncertainty.
dymola project of controlled angular overshoot of a pendulum
An open source library for connecting AnyLogic models with python-based black box optimization packages
Performance-oriented model learning for control via multi-objective Bayesian optimization
A Java package for scientific computing
(GECCO 2023) Natural Evolution Strategy for Mixed-Integer Black-Box Optimization
Benchmark for Biophysical Sequence Optimization Algorithms
A collection and visualization of single objective black-box functions for optimization benchmarking.
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