Logistics Science Award 2026 goes to Timo Lehmann for research on automated storage systems

The outstanding dissertation "Throughput Models and Performance Evaluation for Multi-Deep Automated Storage Systems" focuses on the question of how the performance of automated storage systems with multiple storage depths can be reliably evaluated already during the planning stage.

Such systems enable compact storage of goods and can thus contribute to better space utilization. According to the German Logistics Association, the evaluation of different facility configurations and operational strategies is complex. Until now, elaborate simulations have often been necessary to obtain reliable statements about a system's performance.

Therefore, Lehmann developed analytical methods that allow the throughput capacity of multi-deep automated warehouses to be estimated. With these, warehouse planners can compare different facility concepts and control strategies in early project phases without needing to create a separate simulation model for each variant studied. The models are intended to support the selection of suitable storage strategies and the dimensioning of required capacities. They can be used both in the planning of new facilities and in the evaluation of existing systems.

13 Operational Strategies Systematically Examined

The research examines various types of automated storage systems with multiple storage depths. These include automated storage and retrieval systems as well as robot-assisted storage and retrieval systems. In total, Lehmann modeled, validated, and compared 13 different operational strategies. According to the German Logistics Association, the study also includes the strategy used by AutoStore.

For the mathematical description of the systems, the scientist used Markov chains and closed queuing networks. These methods allow the behavior of the storage systems in stationary operation to be depicted, and their performance under different conditions to be analytically examined. This work thus enables a systematic comparison of various control and storage concepts based on their respective throughput capacity.

Up to 48.5 Percent Higher Throughput

An essential result of the dissertation concerns the impact of the operating strategy on the performance of automated warehouses. The study shows that the selection of appropriate storage and retrieval rules can lead to significant differences in achievable throughput. According to the German Logistics Association, particularly effective was the combination of class-based storage with product-specific retrieval rules. This approach can increase throughput by up to 48.5 percent compared to the standard approaches examined.

The results show that, in addition to the technical system configuration, the chosen operating strategy also has a significant impact on the performance of multi-deep storage systems. The analytical models allow these differences to be examined before implementing a warehouse concept and to compare different strategies in terms of their throughput performance.