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Simulation Based Optimization in Python using Model-based Optimization Algorithm

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SimBO

Simulation Based Optimization in Python using Model-based Optimization Algorithms The Bayesian Optimization Algorithms run with botorch. Normally the newest version of botorch works, except of MorBO, here we need botorch 0.7.0.

Setup and run experiments

Step 1: Install requirement.txt (ATTENTION! No Versions provided - will install the newest):

pip -r requirements.txt

Step 2: Create config.py file in the root directory and set the following variables:

SHEET_ID = "SET YOUR SHEET ID HERE" FIREBASE_CONFIG = "SET YOUR FIREBASE CONFIG PATH HERE" BUCKET = "SET YOUR BUCKET NAME HERE" BIGQUERY_DATASET = "SET YOUR BIGQUERY DATASET NAME HERE" GCLOUD_PROJECT = "SET YOUR GCLOUD PROJECT NAME HERE" GCLOUD_SERVICE_ACCOUNT = "SET YOUR GCLOUD SERVICE ACCOUNT PATH HERE" DB_NAME = "YOU DB NAME"

Step 3: initialize database with:

python backend/databases/init_sql.py

Step 4: Start experiments with:

python main.py 

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