Optimizer limitations

Some complex problems may not result in any feasible or optimal solutions when using Optimizer. This issue can only be detected by running Optimizer.

To minimize the chance of running an optimization with no solution, you can build your dashboard in a way that alerts you to inappropriate values. The 'Ensuring feasibility in the end user dashboard' section of the Transportation Assignment Scenario , demonstrates using a dashboard error alert when demand exceeds supply. Similarly, if negative values aren't appropriate for an optimization, the dashboard can alert the end user.

Optimizer solves only linear problems. Non-linear problems aren't in scope. For example, a transportation scheduling problem during rush hour, where a non-linear increase of vehicle numbers eventually causes exponential delays due to traffic jams.

Optimizer supports using three comparative operators in expressions:

• greater than or equal to (>=)
• equal to (=)
• less than or equal to (<=)

Make sure that all line items in the problem have Time Scale and Versions set as Not Applicable in the Blueprint view. Optimizer doesn't support Time or Versions, so don't include them when inserting modules into your model.

Optimizer provides one solution for each variable when calculating an optimal or feasible solution. The Transportation Assignment Scenario can either determine which products to ship to which retail outlets, or which retail price at which retail outlet brings the most total revenue.

Running an Optimizer process provides the standard Anaplan audit features, so the model history shows who made the changes and when the changes occurred. It doesn't show the before-and-after values.

No undo option is available within Optimizer, but you can restore your model to a historical ID to revert it to a prior state.

Automation of an action that runs the Optimizer isn't supported by Anaplan Connect and the Anaplan API.

Optimizer supports problems where the constraint contains a dimension that is an ancestor of a variable dimension. In lists that have parent-child hierarchies, Optimizer reads only items in the child list.

Optimizer has a time-out setting to prevent the action from running indefinitely until canceled. You can set the time-out in seconds to any time between 1 second and 14,400 seconds (four hours). The default setting is 300 seconds (five minutes). An Optimizer action always ends after four hours, even if you specify a longer time-out.

Workspace administrators can select the Import with timeout setting, so the solution imports even if the action times out before it reaches the specified tolerance (MIPGap %). When this happens, the results summary notifies the user that the optimization timed out and the solution was imported. You can revise the MIPGap and run the action again if needed.

Avoid using Selective Access on lists that are included in the Optimizer problem. This is because Optimizer needs Write access to the top of lists.