Python DOcplex models (Decision Optimization)
You can solve Python DOcplex models in the Decision Optimization model builder.
The basic workflow to create a Python DOcplex model in Decision Optimization and examine it under different scenarios is as follows:
- Create a project.
- Add data to the project.
- Add a Decision Optimization experiment (a scenario is created by default in the experiment UI).
- Select and import your data into the scenario.
- Create or import your Python model.
- Run the model to solve it and explore the solution.
- Copy the scenario and edit the data in the context of the new scenario.
- Solve the new scenario to see the impact of the changes to data.
- Save a model ready for deployment in Watson Machine Learning.