From Rack Configuration to Warehouse Layout Optimization

Generating the optimal pallet-racking configuration is only one part of warehouse design.

The next step is to determine where those racks should be positioned within the warehouse.

We are developing a Python-based warehouse layout optimization tool that takes user-defined warehouse parameters and automatically evaluates different pallet-racking layouts.

How it works

The user defines parameters such as:

• Warehouse length and width
• Staging area
• Rack bay dimensions
• Aisle width
• Back-to-back rack spacing
• Number of rack levels
• Pallets per level
• Layout direction
• Other warehouse constraints

The program then evaluates different possible configurations and generates a visual representation of the warehouse layout.

Instead of manually drawing a layout, adjusting rack positions, and repeatedly counting storage capacity, the optimization process can systematically search for a suitable configuration.

From Parameters to Layout

Input → Calculate → Optimize → Visualize

The objective is to make warehouse layout design more data-driven and reduce the amount of manual trial and error involved in preliminary warehouse planning.

The current development is focused on pallet-racking layouts. Future development can incorporate additional factors such as different rack types, MHE requirements, operational flow, product characteristics, dock locations and other warehouse constraints.

Watch the Development

See how the Python-based warehouse layout optimization works in the video below.

AI-assisted warehouse design — from warehouse parameters to an optimized pallet-racking layout.