Class or Function Names MeanVarianceAnalysisScalarizationSimulatorSampler Installation $ pip install scipy Example Please see example.ipynb
Others For example, you can add sections to introduce a corresponding paper.
Reference Iwazaki, Shogo, Yu Inatsu, and Ichiro Takeuchi. “Mean-variance analysis in Bayesian optimization under uncertainty.” International Conference on Artificial Intelligence and Statistics. PMLR, 2021.
Bibtex @inproceedings{iwazaki2021mean, title={Mean-variance analysis in Bayesian optimization under uncertainty}, author={Iwazaki, Shogo and Inatsu, Yu and Takeuchi, Ichiro}, booktitle={International Conference on Artificial Intelligence and Statistics}, pages={973--981}, year={2021}, organization={PMLR} }
Abstract Sampler using MOEA/D algorithm. MOEA/D stands for “Multi-Objective Evolutionary Algorithm based on Decomposition.
This sampler is specialized for multiobjective optimization. The objective function is internally decomposed into multiple single-objective subproblems to perform optimization.
It may not work well with multi-threading. Check results carefully.
Class or Function Names MOEADSampler Installation pip install scipy or
pip install -r https://hub.optuna.org/samplers/moead/requirements.txt Example import optuna import optunahub def objective(trial: optuna.Trial) -> tuple[float, float]: x = trial.