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Phase 2. Configure and Run Simulation Experiment

In the previous phase we imported scenario with optimized data, added suppliers, which will be servicing our distribution centers, created and configured inventory and sourcing policies.

In this phase we will configure and run Simulation experiment.

Create Simulation experiment

  1. Navigate to the Experiments and click Simulation experiment.

    You will be taken to the Simulation experiment's view with its default settings.

We will define the parameters of the experiment now.

Define Simulation experiment parameters

  1. Click the Product statistics unit drop-down list and select pcs to define the measurement unit to be used in the statistics.

    Proceed to specify statistics that must be collected during the Simulation experiment.

  2. Click Configure statistics to open a dialog box allowing you to select and configure the required statistics.


  3. By default all statistics are enabled. Uncheck all the available statistics to further enable only the ones we need (Total Cost, Available Inventory and Demand Received (Dropped Orders)).
    • Press Ctrl and click the Enabled column title. All toggle buttons referring to the currently available statistics will be selected.
    • Press Spacebar twice to instantly change the state of all toggle buttons. First you will enable the currently disabled statistics, then you will disable all the statistics.

    Now that all the statistics are unchecked, you may either scroll down the whole list of all the available statistics to check the ones we will use during the experiment, or you may filter them by their names.

  4. Type Total Cost in the cell below the Name column title and press Enter to filter the available statistics. You will see the Total Cost statistics of Finances value type.
  5. Click the toggle box to the left of it in the Enabled column to activate data collection for the current statistics.

  6. In the same way check the Available Inventory and Demand Received (Dropped Orders) statistics.
  7. Once you are done with configuring statistics, click OK to close the dialog box.
  8. Click Run in the toolbar of the Simulation experiment.

    The GIS map will appear allowing us to observe the real-time simulation (current model time considering the experiment speed) of the supply chain with shipments (purple dots) shipped from distribution centers to the customers and from the supplier to the distribution centers.

Our next step is to add the statistics that we want to compare. It can be done in the dashboard, which is located in the lower part of the anyLogistix workspace. The dashboard is divided into two areas:

  • The section on the left is displaying the list of available dashboard pages. You can switch between pages, add new pages and remove the existing pages.
  • The contents section on the right is displaying the contents of the currently selected page. The Dashboard page is selected by default (you can rename it if needed by right-clicking and selecting Rename from the pop-up menu).

Add statistics to the dashboard

  1. Right-click the empty content section of the Dashboard page and select Add item from the shortcut menu. The Properties dialog box will open.
  2. Click Expand to the right of the search box to see all the available statistics.

  3. Check the Total Cost statistics in the Finances group of the Statistics selection section. We will leave the offered by default Table chart type selected in the Preview section.

  4. Click OK in the bottom right part of the Properties dialog box. The Total Cost statistics will appear on the dashboard in the form of a table showing the total costs for the current moment.

Now we will add Available Inventory and Demand Received (Dropped Orders) statistics to the dashboard:

  1. Open the Properties dialog box and check the Available Inventory statistics.
  2. Set Line as its visualization method.

  3. Click OK to close the Properties dialog box. The selected statistics will appear on the dashboard in the form of a Line chart to the right of the previously added Total Cost statistics.

  4. In the very same way add the Demand Received (Dropped Orders) statistics to the dashboard:
    • Set its chart type to Table.
    • Navigate to the Additional settings area at the bottom of the dialog box and click the In Total / Per Item toggle button referring to the Object record, allowing us in such a way to monitor statistics per object, i.e., we will see the quantity of orders lost at every warehouse.

    The Preview section will show the updated table view

  5. Click OK to close the Properties dialog box. The dashboard will now show the total cost statistics, the available inventory level (as well as the way it changes over time) and the quantity of lost orders per site.

    On the screenshot below you can see the three statistics that we intended to monitor, with the Demand Received (Dropped Orders) statistics providing data on each DC individually.

Elements added to the dashboard can be rearranged to optimize occupied space.

Take a moment to monitor the collected Available Inventory statistics. You will see that the inventory level increases every time a new shipment from the supplier is received.

Have a closer look at the statistics

  1. Click the Enlarge button in the top-right corner of the Available Inventory chart.

    The chart will be enlarged and placed over the anyLogistix layout.

  2. To get back to the compact view, click Close.

Let us increase the simulation speed and monitor data in the Demand Received (Dropped Orders) table.

Increase the speed of the experiment

  1. Navigate to the toolbar above the GIS map. You will see the speed control element (slider).
  2. Drag the slider to the right to set the speed to x2 value, which will correspond to two model days per second.

  3. Then drag it to the max value. The experiment will be executed much faster and as a result it will be completed in a few seconds.

  4. When simulation is competed, click Stop in the toolbar of the Simulation experiment to stop the experiment.
    A dialog box will appear asking if you would like to save experiment results.

  5. Click Yes. The saved results will be available in the new Statistics item.
  6. Now look at the Demand Received (Dropped Orders) statistics. As you can see, 6 orders were lost at Elko DC, 72 orders were lost at Vicksburg DC and 316 orders were lost at Wilkes-Barre DC. We will have to modify the inventory policy later to eliminate the losses and to fully satisfy the demand.

  7. Lastly, let us take a look at the Total Cost table showing the expenses for all of the distribution centers. As you can see, it constitutes $139,454,141.544.

Alongside the total aggregated cost, we can examine the expenses incurred by each warehouse individually. This can be set in the settings of the dashboard element.

Examine statistics per item

To examine Available Inventory per warehouse, modify the element's parameters:

  1. Click the Change settings button to modify the element's parameters. The Properties dialog box will open.
  2. Define the parameter of the Additional settings section to monitor statistics per object.
  3. Click OK in the bottom right part of the Properties dialog box.

To examine Total Cost per item on a new dashboard element:

  1. Add new Total Cost element and configure it to show data per object.
  2. Click OK to close the Properties dialog box. The selected statistics will appear on the dashboard.

    As compared to configuring the existing element, adding a new element allows you to have two independent dashboard elements offering aggregated total cost of all the objects and total cost per each individual object. We suggest that you should add new element.

Before we proceed, we will add one more Demand Received (Dropped Orders) element showing the total amount of dropped orders for all warehouses.

Add new Demand Received (Dropped Orders) element

  1. Add new Demand Received (Dropped Orders) element and leave the default settings as they are:
    • Visualization type: Table
    • Additional settings: ObjectIn Total
  2. Click OK to close the Properties dialog box. The selected statistics will appear on the dashboard.

Now we can see the results of our simulation experiment in details.

The results clearly show that we have lost certain amount of orders. The orders are dropped primarily because of the Backorder Policy (defined in the Demand table), which is set to Not allowed.

Let us analyze the data on dropped orders and find the moment the first order was lost.

Analyze Demand Received (Dropped Orders) statistics

  1. Adjust the settings of the Demand Received (Dropped Orders) statistics that show data per object.
    • Click the Change settings button to open the Properties dialog box.
    • Set Line as the chart type for the current statistics.
    • Click the Daily / Accumulative toggle button to observe data received per day, rather than the sum of the collected data.

    • Click OK to save the changes and close the Properties dialog box.
  2. Click the Enlarge button in the top-right corner of the Demand Received (Dropped orders) chart.
  3. Click the Horizontal zoom button to activate the tool.
  4. Left-click at the beginning of the chart and drag the mouse to the right to select the horizontal range containing the data on the first lost orders.

    You will zoom in to the selected range. As you can see, 2 orders were lost on the 4th day, which means that the initial amount was not sufficient.

You can run a number of what-if scenarios, adjusting the inventory policy parameters and examining the difference among the numerous received results.

Run what-if scenarios

  1. Navigate to the Inventory table.
  2. Open the pop-up dialog box by double-clicking the Policy parameters cell in the DCs row.
  3. Adjust the Min and Max values by typing in the 2000 and 5000 respectively.
  4. Set the Initial Stock, units to 1500.
  5. Navigate back to the Simulation experiment and run it.
  6. Voila — we have lost no orders, but as you can see, the expenses have increased as well and now constitute $171,197,637.037

We have successfully completed the Simulation experiment.

During this tutorial we learned to configure inventory policies, improved service level by eliminating the possibility of lost orders and executed what-if scenarios to find the optimal product stock volume.

To completely avoid losing orders, save your time on what-if scenarios, minimize the expenses and find the best possible inventory level — you should use the Variation experiment.

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