Collaborative routing problems in automated warehouses
Publication date
2025-12-15
Document type
Preprint
Author
Organisational unit
Institute of Operations Management, University of Hamburg Business School, Hamburg, Germany
Publisher
Universitätsbibliothek der HSU/UniBw H
Part of the university bibliography
✅
Language
English
Keyword
Scheduling
Order picking
Warehouse management
Routing
Collaboration
dtec.bw
Abstract
The pick-and-drive system is a novel solution for warehouse automation. It integrates two types of autonomous mobile robots (AMRs). Storage and supply AMRs (S-AMRs) navigate to a storage area, where they lift unit loads and transport them to a disposition area. Picking AMRs (P-AMRs) move freely within this disposition area. They carry bins and meet S-AMRs to collect items from the unit loads attached to the S-AMRs by means of robotic arms. We take an operational perspective on the pick-and-drive system and focus on the problem of determining and scheduling meeting locations and sequences of the AMRs, so that all required items are picked. This setting is interpreted as a vehicle routing problem, where the customers (S-AMRs) collaborate with the vehicles (P-AMRs). We consider two objective functions, minimizing the total distance driven by the AMRs and minimizing the sum of completion times of the P-AMRs. We translate these routing problems into a mathematical framework and provide theoretical insights by examining a specific case where the potential meeting points lie along a line. For this scenario, we present an approximation algorithm for the case of minimizing the overall distance traveled and demonstrate that minimizing the sum of completion times is strongly NP-complete. Additionally, we prove strong NP-completeness of the general case when minimizing the overall distance traveled. Leveraging the structural insights, we develop heuristics that are evaluated in a numerical study. Our results highlight the potential impact of the system in practice.
Version
Author's original
Access right on openHSU
Open access