Agent-Based Control of Interaction Areas in Intralogistics: Concept, Implementation and Simulation
<i>Background</i>: 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,...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Logistics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2305-6290/9/2/52 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | <i>Background</i>: 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. <i>Methods</i>: 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. <i>Results</i>: The study confirms the viability of agent-based control for managing interaction areas in AGV systems, highlighting trade-offs between decentralization, efficiency, and communication. <i>Conclusions</i>: It offers a foundation for further research into hybrid models and real-world application of decentralized control strategies. |
|---|---|
| ISSN: | 2305-6290 |