This project aims to optimize a reaction with a mixed input domain and multiple objectives.
Code associated with the paper Multi-objective Bayesian optimisation using q-noisy expected hypervolume improvement (q NEHVI) for the Schotten–Baumann reaction.
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Clone the repo
git clone https://github.com/sustainable-processes/bo_mixed.git
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Create a virtual environment and install the dependencies
python3 - m venv .venv source .venv/bin/activate pip install -r requirements.txt
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Run the code
python main.py
You can see a full list of commands by running python main.py --help
. Some examples:
# Use TSEMO as a strategy
python main.py --strategy MOBO
# Use TSEMO as a strategy
python main.py --strategy TSEMO
# Pass your own initialization data and don't run LHS initialization
python main.py --initialization-data-path data.csv --num-initial-experiments=0