How to Understand the Difference Between Discrete Event and Monte Carlo Simulators

Published by on July 8, 2015 at 12:58 pm.

How to Series Part 1: Beginner Innoslate

Risk Analysis is a part of every decision we make. Uncertainty, ambiguity, and variability are in constant flux as we move along in projects and try to determine the risk in each scenario we encounter. This is the purpose of the Monte Carlo Simulator.

In every simulation whether Monte Carlo or Discrete Event, we need something to simulate. Remember the drag and drop article? Well now is the time to create your action diagram and simulate it.

Action Model

Our Action Model to Simulate


I could spout off the ideal definition here and that would be a great segue into this next paragraph but the best explanation of the Monte Carlo simulator is that it provides us with a statistical range of possible outcomes and the likelihood that they occur for any choice of actions in our diagrams. Innoslate Monte Carlo simulations use data within the entities and models to determine the likeliness of how things will transpire from your models.


Monte Carlo Output of Duration or Average Time

Monte Carlo Output of Duration or Average Time


Monte Carlo Simulation is a very powerful tool for Program and Project Managers, as well as Systems Engineers. Innoslate’s Monte Carlo simulation provides histograms that display duration values and time constraints, cost charts broken down by individual cost values by resource or event, total simulation cost, resource acquisition and the breakdown of availability during the simulations as well as the cost constraints put on the budget by the resources and when to allocate more.


Monte Carlo B

Cost Output from the Monte Carlo Simulation


Discrete event simulation is a simple concept which models the system as a discrete sequence of events. In this case we are simulating one sequence of the model. Of course we can use scripting to manipulate the outcomes, but that is not what we are focusing on here.

Discrete event simulation in Innoslate will provide a Gantt chart result to reflect time, cost, and decisions made during the simulation. The output will also provide the resources used during the simulation and where the gaps are in resources used during the event.


Gantt Chart Output of Discrete Event Simulation

Gantt Chart Output of Discrete Event Simulation



To access the discrete event simulator, access your action diagram and select the blue “Simulate” button at the top. Select discrete event, which will bring you to the simulator screen.

To run the simulator, click on the green arrow and away you go. You can also use the drop down arrow to select to automate or prompt the decisions.


Discrete Event Cost Graph

Discrete Event Cost Graph









Monte Carlo Simulation is selected the same way and will run the same way, yet it takes a bit longer as the model is run numerous times to predict more accurate outcomes.

Whether you want to run a single sequence of events or a prediction simulation, Innoslate provides both methods of simulation. Monte Carlo was developed during WWII and has been in use ever since while Discrete Event shortly followed thereafter. Both are very powerful and helpful tools in the world of modeling and simulation. Innoslate provides both for the user and the valuable data produced allows for better accuracy and tracking of assets during a project, ensuring your models are accurate all while keeping costs low and efficiency high.