Petri Net Modeling and Deadlock-Free Scheduling of Attachable Heterogeneous AGV Systems

2025-08-01

AI Summary

To address deadlock risks and scheduling complexity in collaborative transportation involving connectable heterogeneous AGVs (carriers and shuttles), this paper proposes a Petri net–based cooperative scheduling method. We innovatively design a trigger-driven decoding mechanism that models AGV connection/separation dynamics as Petri net transitions, integrated with online deadlock detection and prevention. Furthermore, we develop a Petri net–guided adaptive large neighborhood search (ALNS) metaheuristic, incorporating acceleration techniques and dependency-aware neighborhood operators. Experiments on real industrial data demonstrate that our approach significantly outperforms engineering heuristics, exact solvers, and four state-of-the-art metaheuristics—achieving superior performance in scheduling efficiency, safety, and robustness. It also enables optimization of management decisions under connectivity constraints.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Metareasoning and Metaheuristics
• Multiagent Systems: Coordination and Collaboration

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

The increasing demand for automation and flexibility drives the widespread adoption of heterogeneous automated guided vehicles (AGVs). This work intends to investigate a new scheduling problem in a material transportation system consisting of attachable heterogeneous AGVs, namely carriers and shuttles. They can flexibly attach to and detach from each other to cooperatively execute complex transportation tasks. While such collaboration enhances operational efficiency, the attachment-induced synchronization and interdependence render the scheduling coupled and susceptible to deadlock. To tackle this challenge, Petri nets are introduced to model AGV schedules, well describing the concurrent and sequential task execution and carrier-shuttle synchronization. Based on Petri net theory, a firing-driven decoding method is proposed, along with deadlock detection and prevention strategies to ensure deadlock-free schedules. Furthermore, a Petri net-based metaheuristic is developed in an adaptive large neighborhood search framework and incorporates an effective acceleration method to enhance computational efficiency. Finally, numerical experiments using real-world industrial data validate the effectiveness of the proposed algorithm against the scheduling policy applied in engineering practice, an exact solver, and four state-of-the-art metaheuristics. A sensitivity analysis is also conducted to provide managerial insights.

Problem

• Modeling attachable heterogeneous AGV systems to prevent deadlock
• Developing deadlock-free scheduling using Petri nets and metaheuristics
• Validating algorithm effectiveness with real-world industrial data

Innovation

• Petri nets model AGV schedules and synchronization
• Firing-driven decoding with deadlock prevention strategies
• Petri net-based metaheuristic in adaptive search framework