Many-to-Many Multi-Agent Pickup and Delivery

2026-05-08

AI Summary

This study addresses the many-to-many multi-agent pickup and delivery (MAPD) problem in automated warehouses, where items can be retrieved from or delivered to multiple locations—a realistic yet NP-hard four-dimensional assignment problem. The work presents the first systematic extension of traditional one-to-one MAPD to this more practical many-to-many setting. To tackle it, the authors propose the M2M algorithm and its variant M2M-wSKU, which jointly optimize task assignment, path coordination, and leverage SKU inventory distribution information—either minimizing task makespan or incorporating prior knowledge of SKU locations. Experimental results demonstrate that, over an 8-hour simulation horizon, M2M consistently outperforms the current state-of-the-art across varying warehouse densities, completing up to 22,000 additional tasks.

Abstract

Multi-robot systems in automated warehouses must manage continuous streams of pickup-and-delivery tasks while ensuring efficiency and safety. Prior work on Multi-Agent Pickup-and-Delivery (MAPD) has largely focused on the one-to-one variant, where each task has a fixed pickup and delivery location. In contrast, real warehouses often present many-to-many MAPD scenarios, where items, tracked by stock keeping unit (SKU) identifiers, can be retrieved from or stored at multiple locations, resulting in an NP-hard four-dimensional assignment problem. To solve the many-to-many MAPD problem, we contribute our algorithm: Many-to-Many Multi-Agent Pickup and Delivery (M2M). We experiment with two variants of our algorithm: one that minimizes estimated task durations (M2M), and one which incorporates SKU distribution into the objective function (M2M-wSKU). Simulation results over 8-hour warehouse operations show that our method consistently matches or outperforms prior state of the art, with M2M completing up to 22,000 more tasks on average across different environments and warehouse inventory densities.

Problem

• Many-to-Many MAPD
• Multi-Agent Pickup and Delivery
• SKU
• Automated Warehouse
• Task Assignment

Innovation

• Many-to-Many MAPD
• Multi-Agent Path Finding
• SKU-aware Scheduling
• Four-Dimensional Assignment
• Automated Warehouse