Efficient warehouse operations require companies to determine where thousands of different items should be stored while balancing product characteristics, storage capacity, picking routes, and changing demand.

In this webinar, experts from Arvato, a global supply chain and logistics services provider specializing in scalable, technology-driven fulfillment solutions, will share how they developed a mixed-integer linear programming model to optimize the spatial allocation of items within warehouse operations. The model considers factors such as item velocity, pick-path routing, capacity limitations, and product characteristics to support more efficient allocation decisions.

Attendees will gain practical insights into translating daily operational challenges into scalable algorithms, integrating Gurobi into production workflows, and achieving measurable improvements in operational efficiency and fulfillment throughput.

You’ll also hear how Arvato integrated Gurobi into its production workflows and developed scalable optimization algorithms for real-world fulfillment operations. The speakers will discuss their approach, implementation experience, and how mathematical optimization can help reduce travel distances, improve storage utilization, and increase operational efficiency and throughput.

Whether you are exploring mathematical optimization for the first time or looking for practical ways to improve your own warehouse operations, this session will provide valuable insights into turning complex operational requirements into production-ready optimization solutions.