The Multiagent Pathfinding Problem involves determining optimal, collision-free routes for a fleet of multiple autonomous vehicles from current positions to prescribed (goal) positions within a transportation or logistics facility such as a port terminal or a warehouse. This paper describes an exact algorithm for the problem, in which a sequence of reduced Mixed Integer Programming problems is solved iteratively on suitably defined time-expanded networks until an optimal solution is found. Computational results show that our approach outperforms a state-of-the-art solution algorithm on various mediumand large-sized instances. Additionally, we provide several managerial insights.

Solving the multiagent pathfinding problem with time-expanded networks.

Tommaso Adamo;Gianpaolo Ghiani;Emanuela Guerriero
2025-01-01

Abstract

The Multiagent Pathfinding Problem involves determining optimal, collision-free routes for a fleet of multiple autonomous vehicles from current positions to prescribed (goal) positions within a transportation or logistics facility such as a port terminal or a warehouse. This paper describes an exact algorithm for the problem, in which a sequence of reduced Mixed Integer Programming problems is solved iteratively on suitably defined time-expanded networks until an optimal solution is found. Computational results show that our approach outperforms a state-of-the-art solution algorithm on various mediumand large-sized instances. Additionally, we provide several managerial insights.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/575229
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