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
Safe Explorative Bayesian Optimization -- Towards Personalized Treatments in Plasma Medicine
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.
Derivative-free solver for the minimization of a function over the convex hull of a set of vectors
Object-Orientated Derivative-Free Optimisation
Python implementation of Scalable Combinatorial Bayesian Optimization with Tractable Statistical Models
Code for Dividing Rectangles Attack Multi-Objective Optimization
Black-box optimization for real-world scenario
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
dymola project of controlled angular overshoot of a pendulum
A Java package for scientific computing
(GECCO 2023) Natural Evolution Strategy for Mixed-Integer Black-Box Optimization
A collection and visualization of single objective black-box functions for optimization benchmarking.
A deterministic global optimization algorithm for black-box problems.
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