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2244. Scheduling and conflict-free routing of automated guided vehicles in container terminals
Invited abstract in session MA-62: Seaside Planning I, stream OR in Port Operations.
Monday, 8:30-10:00Room: S12 (building: 101)
Authors (first author is the speaker)
1. | Mohamed Ben Ahmed
|
Faculty of Logistics, Molde University College | |
2. | Steffen Bakker
|
Industrial Economics and Technology Management, NTNU | |
3. | Kjetil Fagerholt
|
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology |
Abstract
In automated container terminals, automated guided vehicles (AGVs) are used to transport containers from the quayside to their location in the storage area. AGVs navigate between key terminal locations, following predefined guide paths. They have bidirectional movement capabilities that enable forward and backward travel, and their movements remain predominantly linear, aligning with the terminal’s layout. Limited buffer space at pickup and drop-off points causes AGVs to wait until ongoing operations conclude, creating delays. Delays may also occur when a quay crane must wait for an AGV. Therefore, minimizing both the delay times of QCs and the travel time of AGVs is vital for reducing vessel dwell time and enhancing operational efficiency. AGV conflicts, like deadlocks and collisions, worsen delays, causing congestion and decreased throughput. Implementing advanced routing algorithms and control systems is thereby essential to optimize AGV movements and enhance operational efficiency. This work presents a time-space network formulation for the problem scheduling and routing of AGVs in container terminals where conflict avoidance constraints are explicitly modeled. The problem’s objective is to minimize the vessel’s dwell time while ensuring the smooth flow of container handling operations. A solution method that combines a mathematical formulation and an insertion heuristic is implemented. Testing and validation are conducted using real data from Norwegian port cases.
Keywords
- Logistics
- Mathematical Programming
- Maritime applications
Status: accepted
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