EURO 2024 Copenhagen
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1722. Swarm or System-directed? Analysis of Human-Robot Matching Policies in Collaborative Order Pick Systems

Invited abstract in session MD-50: Warehouse Management, stream Retail Operations.

Monday, 14:30-16:00
Room: M2 (building: 101)

Authors (first author is the speaker)

1. Mahdi Ghorashi Khalilabadi
Technology and Operations Management, Rotterdam School of Management
2. Debjit Roy
Production and Quantitative Methods, Indian Institute of Management Ahmedabad
3. René de Koster
Rotterdam School of Management, Erasmus University Rotterdam

Abstract

Autonomous Mobile Robots (AMRs) collaborate with humans in order-picking and can increase order-picking efficiency by reducing walking. AMRs can operate under two policies: Swarm or System-Directed. This study models the Swarm policy using a closed queuing model to determine system throughput capacity. The queuing model incorporates AMR-picker matching via a synchronization station. We derive closed-form expressions for network steady states and use these to calculate order throughput. The impact of various factors on overall system performance is analyzed such as order profiles, matching policies (closest or random), AMR and picker speeds, warehouse size, item assignment methods, and AMR-to-picker ratios. Furthermore, we compare the order throughput of the swarm with the system-directed policy to ascertain superior performance under different circumstances. Results indicate that the swarm policy generally outperforms, particularly at higher AMR-to-picker speed ratios. However, its effectiveness diminishes with larger order sizes and lower AMR-to-picker ratios. Overall, the study provides insights into optimizing e-commerce warehouse operations through effective decision-making in swarm collaboration, aiming to enhance productivity and efficiency in order fulfillment.

Keywords

Status: accepted

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