What's new and changed in Decision Optimization

Decision Optimization updates can include new features, bug fixes, and security updates. Releases are listed in reverse chronological order so that the latest release is at the beginning of the topic.

You can see a list of the new features for the platform and all of the services at What's new in IBM Cloud Pak for Data.

Installing or upgrading Decision Optimization

Ready to install or upgrade Decision Optimization?

To install Decision Optimization along with the other Cloud Pak for Data services, see Installing Cloud Pak for Data.
To upgrade Decision Optimization along with the other Cloud Pak for Data services, see Upgrading Cloud Pak for Data.
To install or upgrade Decision Optimization independently, see Decision Optimization.
Remember: All of the Cloud Pak for Data components associated with an instance of Cloud Pak for Data must be installed at the same version.

Cloud Pak for Data Version 5.0.3

A new version of Decision Optimization was released in September 2024 with Cloud Pak for Data 5.0.3.

Operand version: 9.3.0

This release includes the following changes:

Security issues fixed in this release

The following security issues were fixed in this release:

CVE-2024-42461, CVE-2024-42460, CVE-2024-42459, CVE-2024-41818, CVE-2024-41110, CVE-2024-4067, CVE-2024-4032, CVE-2024-39689, CVE-2024-39338, CVE-2024-36137, CVE-2024-2398, CVE-2024-22020, CVE-2024-22018.

See https://exchange.xforce.ibmcloud.com/ for details.

Cloud Pak for Data Version 5.0.1

A new version of Decision Optimization was released in July 2024 with Cloud Pak for Data 5.0.1.

Operand version: 9.1.0

This release includes the following changes:

Security issues fixed in this release

The following security issues were fixed in this release:

CVE-2024-4068, CVE-2024-37891, CVE-2024-37890, CVE-2024-3727, CVE-2024-35195, CVE-2024-33602, CVE-2024-33601, CVE-2024-33600, CVE-2024-33599, CVE-2024-2961, CVE-2024-28182, CVE-2024-0450,

CVE-2023-6597.

See https://exchange.xforce.ibmcloud.com/ for details.

Deprecated features

The following features were deprecated in this release:

Python 3.10 is deprecated

Python is used to run and deploy Decision Optimization models formulated in DOcplex in Decision Optimization experiments. Modeling Assistant models also use Python because DOcplex code is generated when models are run or deployed.

The Decision Optimization environment currently supports Python 3.11 and 3.10. The default version is Python 3.11. Python 3.10 is deprecated.

For more information about updating your environment, see Configuring environments.

For more information about updating existing deployed models, see Changing Python version for an existing deployed model with the REST API.

Cloud Pak for Data Version 5.0.0

A new version of Decision Optimization was released in June 2024 with Cloud Pak for Data 5.0.0.

Operand version: 9.0.0

This release includes the following changes:

New features

This release of Decision Optimization includes the following features:

Easier table selection and configuration options when saving Decision Optimization models for deployment

When you save a model for deployment from the Decision Optimization user interface, you can now review the input and output schema, and more easily select the tables that you want to include. You can also add, modify or delete run configuration parameters, review the environment, and the model files used.

Save model for deployment dialog open with input output schema displayed.

For more information, see Deploying a Decision Optimization model by using the user interface.

Download intermediate solution statistics for Decision Optimization

If you choose to display intermediate solutions in your run configuration, you can now download the statistics when a Decision Optimization solve is completed. You can view these statistics locally and compare them with other model solutions. You can also view the last 3 intermediate solution KPIs in the Explore solution view.

For more information, see Intermediate solutions in a Decision Optimization experiment.

Use pivot tables to display data aggregated in Decision Optimization experiments

You can now use pivot tables to display both input and output data aggregated in the Visualization view in Decision Optimization experiments.

For more information, see Pivot table widgets

Python 3.11 is now available

In addition to Python 3.10, you can now use Python 3.11 in your Decision Optimization environment to run and deploy Decision Optimization models that are formulated in DOcplex in Decision Optimization experiments. Modeling Assistant models also use Python because DOcplex code is generated when models are run or deployed.

You can update your Python version as follows:

When creating and running models, see Configuring environments.
For existing deployed models, see Changing Python version for an existing deployed model with the REST API.

Security issues fixed in this release

The following security issues were fixed in this release:

CVE-2024-34064, CVE-2024-27983, CVE-2024-27982, CVE-2024-22025, CVE-2024-22019, CVE-2024-22017, CVE-2024-21896, CVE-2024-21892, CVE-2024-0727,

CVE-2023-46809,

CVE-2022-48554, CVE-2022-26336,

CVE-2019-11358,

CVE-2018-20677, CVE-2018-20676, CVE-2018-14042,

CVE-2012-6708.

See https://exchange.xforce.ibmcloud.com/ for details.