Creating a Decision Optimization experiment

Last updated: Nov 21, 2024

This example shows you how to create a Decision Optimization experiment.

Before you begin

Requirements

To edit and run Decision Optimization models, you must have the following prerequisites:

Admin or Editor roles: You must have Admin or Editor roles in the project. Viewers of shared projects can only see experiments, but cannot modify or run them

watsonx.ai Runtime service: You must have a watsonx.ai Runtime service that is associated with your project. You can add one when you create a Decision Optimization experiment.

Deployment space: You must have a deployment space that is associated with your Decision Optimization experiment. You can choose a deployment space when you create a Decision Optimization experiment.

You can create a Decision Optimization experiment from scratch or from a sample file.

To create a Decision Optimization experiment:

Open your project or create an empty project.
Select the Assets tab.
Select New asset > Solve optimization problems in the Work with models section.
In the Create a Decision Optimization experiment window that opens, enter a name to create a model from scratch. You can alternatively choose Local file and select a .zip file to upload an existing experiment.
If you haven't already associated a watsonx.ai Runtime service with your project, you must first select Add a Machine Learning service to select or create one before you choose a deployment space for your experiment.
Click New deployment space, enter a name, and click Create (or select an existing space from the drop-down menu).
Click Create.

A Decision Optimization experiment is created that contains Scenario 1. (Alternatively, if you choose a local file, the experiment scenarios open).