You can select various run parameters for the optimization solve in the Decision Optimization experiment UI.
CPLEX runtime version
As CPLEX engine performance improves with each new version, older versions are deprecated and
removed over time. Runtimes, based on these engines, are used in building and deploying Decision
Optimization models. Currently, the do_22.1 runtime,
based on CPLEX 22.1 is used automatically when you create and run
scenarios. The do_20.1 runtime based on CPLEX
20.1 is also available. You can view and change your CPLEX runtime in
the experiment Overview.
Open the Environment tab of the Information pane and select one of the
available environments for your type of model (Python, OPL, CPLEX, CPO). See Overview for more
details.
Python version
You can view and change the Python environment in the experiment Overview on the Environment tab of the Information pane. For more information, see Overview and Configuring environments and adding Python extensions.
Run configuration parameters
When you click the Configure run icon 
next
to the Run button in the Build model
view, a window opens showing you the currently
set parameter values.
You can click Add parameter and then choose from the following parameters from the Select Parameters drop-down menu.
| Name | Type | Description |
|---|---|---|
Runtime limit |
Number | You can use this parameter to set a time limit in seconds. |
Log detail level
|
Enum
|
You can use this parameter to define the level of detail provided by the engine log. The
default value is INFO. |
Job memory |
Number | You can use this parameter to set a job memory limit in MB. |
Intermediate solution delivery |
Enum
|
You can use this parameter to obtain a sample of intermediate solutions while the solve is
running. The default value is NO, which means that no
intermediate solutions are displayed. To see intermediate solutions, set this parameter to a
frequency. When set, you can see intermediate solutions by clicking New data
available in the graphical display that is shown during the run. The following values,
which are sampled with the frequency you set, are then displayed.
|
IntermediateSolutions sample in the
Model_Builder folder of the DO-samples in the Decision Optimization GitHub. Select the relevant
product and version subfolder.If you choose Custom parameter from the Select Parameters drop-down menu, you can add the following advanced parameters.
| Name | Description |
|---|---|
| Modeling Assistant only For CPLEX
For
CPO |
Python names for CPLEX and CPO parameters can be entered with the prefixes
ma.cplex.parameters. or ma.cpo.parameters.For example,
For a list of parameters see:
|
After you set the run configuration parameters, they will be used with those values for all subsequent runs for that scenario.
You can remove set parameters by hovering over the parameter and clicking the Remove icon.
Environment for scenario
The Environment tab in this pane shows you the default
run environment that is being used for your experiment. 
The Decision Optimization environment currently supports Python 3.10. The default version is Python 3.10.
See the EnvironmentAndExtension example in the Model_Builder folder of the DO-samples in the Decision Optimization GitHub. This example uses an environment with an extension that contains a library file and YAML code.
You can also select a different run environment for a particular scenario, without changing the default for all the other scenarios. See Selecting a different run environment for a particular scenario for more details.
See also Environment tab in Overview information pane and Hardware and software configuration.