Release 3, Sprint 42

This sprint culminates almost eight months of progress. The next 25 pages describe the hundreds of new features that have been added since Version 2. In this latest sprint we have a few important features as well as bringing together the last 11 sprints into a cohesive major release. Overall, you will find that Simio Version 3:

  • empowers novice users through additions and enhancements to the standard library
  • brings greater flexibility to power users with new process steps
  • is easier to learn with improvements to UI, SimBits and learning materials
  • has improved experimentation with ranking and selection tools, and OptQuest
  • provides better understanding of output data with SMORE plots, resource statistics, units support and better reports, and
  • gives advanced users sophisticated tools for search, remove, and interrupt, many new functions, and an improved API.

In Sprint 42:


It was a long time coming and it took many sprints of effort, but you prioritized it so we have it – comprehensive undo and redo capability across the product to make it easier to safely explore and to recover from any accidents. You will notice undo and redo buttons on the quick access toolbar on the upper left. Ctrl-Z and Ctrl-Y also work.


Simio now includes OptQuest from OptTek Systems. OptQuest is the marketing leading tool designed to use simulation to search for optimal solutions. OptQuest uses methods that integrate state-of-the-art metaheuristic procedures, including Tabu Search, Neural Networks, Scatter Search, and Linear/Integer Programming, into a single composite method. In short, Simio is great at modeling your problem and evaluating a proposed solution. OptQuest is great as using that same model to evaluate lots of possible solutions to help you make the best choice.

OptQuest is included in demonstration mode for all users. Commercial users can obtain OptQuest activation for a separate fee. Student and Academic licenses include the full unlimited-size version of OptQuest (limited to non-commercial use).

Report Categories

We revised our reporting categories for clarity. The new categories include: Content, Throughput, Capacity, FlowTime, and HoldingTime. Taking advantage of the pivot table capabilities to sort and filter on these categories will help you more effectively analyze your data.


Limited support is now provided for including non-numeric Controls (e.g. Model Properties) in an experiment.

Queue Names

Each station element has queue holding the entity objects physically located in the station location. The name of that queue used to be'InProcess'. However, as we enhanced Simio's resource state tracking and utilization statistics and the term “Processing” became more prevalent, confusion related to using'InProcess' for that queue name increased as well. The old queue names still exist and are valid, but are no longer in the interface or documented. Instead you will now see:

  • 'InProcess' queue of a station was renamed to'Contents' – Server1.InputBuffer.InProcess is now Server1.InputBuffer.Contents, Server1.Processing.InProcess is now Server1.Processing.Contents.
  • 'BatchQueue' queue of an entity renamed to'BatchMembers' – So the UnBatch step Quantity default for example now is'Entity.BatchMembers'.
  • 'Node.InputLocation.NumberInProcess' renamed to'Node.InputLocation.NumberInLocation'

Seize Behavior

The Seize step was enhanced to dynamically evaluate the quantity (Units Per Object or Number Of Objects ). Among other things, this makes it possible to now Seize resources where the desired quantity to seize is in some Min to Max range…by entering the Units Per Object or Number Of Objects in the form'Math.Max(MinimumDesiredQuantity, Math.Min(Resource.Capacity.Remaining, MaximumDesiredQuantity))'.

New SimBit

SourceServerSinkApproaches.spfx illustrates three different approaches for building a simple model. This is useful for studying the Process approaches versus the standard library approach. It also provides a useful tool for helping students learn to importance of accounting for variability in model data.

Error Checking

We found some common modeling errors coming our way, so we added a bit more robustness to our error checking. If you had previously undetected modeling errors you will need to fix them before running (see Known Anomalies link on Start Page).