Agent-based control of interaction areas in intralogistics
Concept, implementation and simulation
Publication date
2025-04-14
Document type
Forschungsartikel
Organisational unit
Publisher
MDPI
Series or journal
Logistics
ISSN
Periodical volume
9
Periodical issue
2
Article ID
52
Peer-reviewed
✅
Part of the university bibliography
✅
Funding(s)
Language
English
Keyword
Agent-based control
Automated guided vehicles
Autonomous robots
Collision avoidance
Multi-agent systems
Abstract
Background:
Intralogistics systems face growing challenges from globalization, individualization, and shorter product life cycles, demanding flexible and responsive solutions beyond traditional centralized control. Decentralized, agent-based approaches offer potential advantages, especially for Automated Guided Vehicle (AGV) systems where managing collisions in interaction areas remains a critical issue.
Methods:
This study proposes two decentralized, agent-based control concepts for AGV systems in intralogistics. One uses a hierarchical model with an Intersection Manager to coordinate AGV agents, while the other employs a fully heterarchical system. For benchmarking, a First Come, First Served heuristic and a Mixed-Integer Linear Programming (MILP) method are also implemented. Simulations show both agent-based approaches effectively prevent collisions and uphold order prioritization and timing goals. While average delays are similar, the heterarchical system requires up to 2.7 times more communication. Priority-based control enhances timeliness for highpriority vehicles but can increase delays for lower-priority AGVs. The MILP method, though effective, is limited by impractical computation times.
Results:
The study confirms the viability of agent-based control for managing interaction areas in AGV systems, highlighting trade-offs between decentralization, efficiency, and communication.
Conclusions:
It offers a foundation for further research into hybrid models and real-world application of decentralized control strategies.
Intralogistics systems face growing challenges from globalization, individualization, and shorter product life cycles, demanding flexible and responsive solutions beyond traditional centralized control. Decentralized, agent-based approaches offer potential advantages, especially for Automated Guided Vehicle (AGV) systems where managing collisions in interaction areas remains a critical issue.
Methods:
This study proposes two decentralized, agent-based control concepts for AGV systems in intralogistics. One uses a hierarchical model with an Intersection Manager to coordinate AGV agents, while the other employs a fully heterarchical system. For benchmarking, a First Come, First Served heuristic and a Mixed-Integer Linear Programming (MILP) method are also implemented. Simulations show both agent-based approaches effectively prevent collisions and uphold order prioritization and timing goals. While average delays are similar, the heterarchical system requires up to 2.7 times more communication. Priority-based control enhances timeliness for highpriority vehicles but can increase delays for lower-priority AGVs. The MILP method, though effective, is limited by impractical computation times.
Results:
The study confirms the viability of agent-based control for managing interaction areas in AGV systems, highlighting trade-offs between decentralization, efficiency, and communication.
Conclusions:
It offers a foundation for further research into hybrid models and real-world application of decentralized control strategies.
Description
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Published version
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