Configuring the run parameters for a scenario in a Decision Optimization experiment

You can configure the run parameters for all scenarios in a Decision Optimization experiment. Configuring parameters might be useful, for example, for specifying limits for the runtime, for the job memory or for indicating whether you want to see intermediate solutions or not.

When you click the Run configuration icon Configure run icon next to the Run button in the Prepare data, Build model, or the Explore solution view, a window opens showing you the currently set parameter values.

In this window, you can select and edit different run configuration parameters.

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 `OFF` `INFO` `FINE`	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 `NO` `Every minute` `Every 2 minutes` `Every 5 minutes` `Every 10 minutes` `Every 15 minutes`	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. Statistics for a maximum of 3 intermediate solutions. KPIs for a maximum of 3 intermediate solutions. The solution table that shows only values from the last sampling.

See the 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

Name	Description
Modeling Assistant only For CPLEX `ma.cplex.parameters.<Python cplex parameter name>` For CPO `ma.cpo.parameters.<Python cpo parameter name>`	Python names for CPLEX and CPO parameters can be entered with the prefixes `ma.cplex.parameters.` or `ma.cpo.parameters.` For example, `ma.cplex.parameters.mip.tolerances.absmipgap` `ma.cpo.SearchType` For a list of parameters see: CPLEX parameters CPO parameters (Python names do not need IloCP prefixes) and a summary of DOcplex.cp parameters.

Modeling Assistant only

For CPLEX ma.cplex.parameters.<Python cplex parameter name>

For CPO ma.cpo.parameters.<Python cpo parameter name>

Python names for CPLEX and CPO parameters can be entered with the prefixes ma.cplex.parameters. or ma.cpo.parameters.

For example,

ma.cplex.parameters.mip.tolerances.absmipgap

ma.cpo.SearchType

For a list of parameters see:

CPLEX parameters
CPO parameters (Python names do not need IloCP prefixes) and a summary of DOcplex.cp parameters.

After you set the run configuration parameters, these values will be used for all subsequent runs for that scenario.

You can remove set parameters by hovering over the parameter and clicking the Remove icon.