Python DOcplex models

You can solve Python DOcplex models in a Decision Optimization experiment.

The Decision Optimization environment currently supports Python 3.11 and 3.10 (deprecated). The default version is Python 3.11. You can modify this default version on the Environment tab of the Run configuration pane or from the Overview information pane. For more information, see Changing default environments and adding Python extensions for additional Python libraries.

The basic workflow to create a Python DOcplex model in Decision Optimization, and examine it under different scenarios, is as follows:

1. Create a project.
2. Add data to the project.
3. Add a Decision Optimization experiment (a scenario is created by default in the experiment UI).
4. Select and import your data into the scenario.
5. Create or import your Python model.
6. Run the model to solve it and explore the solution.
7. Copy the scenario and edit the data in the context of the new scenario.
8. Solve the new scenario to see the impact of the changes to data.
9. Save a model ready for deployment in Watson Machine Learning.

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