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<i title="Periodica Polytechnica Budapest University of Technology and Economics">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gwmwjkrt5nbupnf3vodblvmmmi" style="color: black;">Periodica Polytechnica Transportation Engineering</a>
This work tackles the problem of controlling operations at an automated container terminal. In the context of large supply chains, there is a growing trend for increasing productivity and economic efficiency. New optimization models and algorithms are provided for scheduling and routing equipment that is moving containers in a quay area, loading/unloading ships, transporting them via Automated Guided Vehicles (AGVs) to Automated Stacking Cranes (ASCs), organizing them in stacks. In contrast<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3311/pptr.8620">doi:10.3311/pptr.8620</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lpdflzon55gphdncuyafiacugy">fatcat:lpdflzon55gphdncuyafiacugy</a> </span>
more »... the majority of the approaches in the related literature, this work tackles two dynamics of the system, a discrete dynamic, characteristic of the maximization of operations efficiency, by assigning the best AGV and operation time to a set of containers, and a continuous dynamic of the AGV that moves in a geographically limited area. As an assumption, AGVs can follow free range trajectories that minimize the error of the target time and increase the responsiveness of the system. A novel solution framework is proposed in order to tackle the two system dynamics. Various metaheuristic algorithms are tested to solve the problem in a near-optimal way. Computational experiments are presented in order to show the feasibility of the proposed framework on a practical case study, and to assess the performance of advanced scheduling and routing algorithms on numerous system settings.
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