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SIM Distribution Network Inside 4 Walls

In this example, we will be using an extension in anyLogistix, which illustrates the behavior of the warehouse in detail. Also, we will see how to customize the warehouse model using an extension to get better performance of the supply chain.

Input data

We consider a supply chain comprising:

  • 1 supplier delivering laptops
  • Customers in the 50 largest cities of Germany
  • DCs in Heidelberg and Hannover
Extension explanation

The advantage of anyLogistix is the ability to extend any object using AnyLogic simulation software built-in as an extension editor.

In this example, we are using the DC with Storages extension of the warehouse model with the site operations inside four walls. It helps us to analyze the actual lifecycle of the product in the warehouse. We can define default settings for each DC by opening the Additional parameters cell in the DCs and Factories table.

The warehouse is divided into several zones. The products delivered by the trucks are placed into the unloading zone where every product is registered and marked. After that, the products are moved to the placement zone by workers. Then forklift trucks transfer products to the specified place in the storage zone, where they are kept.

For each order a warehouse receives, a forklift picks a single pallet from the storage and transports it to the dispatch area. The controlling staff of this area matches the pallet contents with the order. A lorry later drives into the warehouse and takes the pallet out of the warehouse. The zone and staff utilization data are collected and visualized.

This scheme represents the DC with Storages facility. We can open this scheme for any object of this type during the simulation runtime by selecting the required object on the map and clicking the Show animation link.

Below the warehouse layout, we can change parameters to customize the warehouse. We can set the number of workers and forklift trucks, the min and max loading and unloading times.

All changes will affect this facility only.

By changing these parameters during the runtime of the experiment, the actual changes will happen in the warehouse model and will be visually noticeable (workers and forklift numbers change).


Find the best combination by fiddling with the editable parameters, which will provide the best service level, but will use the lowest amount of stuff needed.


To analyze the result of applying different combinations of parameters to the warehouse we can observe the ELT Service Level statistics.

This extension also provided two additional statistics, which we can observe in the dashboard of the Simulation experiment in the Utilization tab:

  • Staff Utilization — shows statistics on the ratio of the occupied to the total staff (can be collected per stuff type).

  • Space Utilization — shows statistics on the ratio of the occupied to the total available space (can be collected per warehouse zone).

  • Available staff — shows statistics on the amount of available staff at a site (can be collected per staff type).

These statistics help us to better understand the actual utilization of warehouse resources and check if the combinations of parameters, applied in the warehouse models, can be improved. The closer ratios to 1 are, the better the found solution is.

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