Simultaneous Allocation and Scheduling of Quay Cranes, Yard Cranes, and Trucks in Dynamical Integrated Container Terminal Operations

We present a dynamical modeling of integrated (end-to-end) container terminal operations using finite state machine (FSM) framework where each state machine is represented by a discrete-event system (DES) formulation. The hybrid model incorporates the operations of quay cranes (QC), internal trucks...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2022-07, Vol.23 (7), p.8564-8578
Main Authors: Cahyono, Rully Tri, Kenaka, Saskia Puspa, Jayawardhana, Bayu
Format: Article
Language:English
Subjects:
Algorithms
Containers
Cranes
Discrete event systems
discrete-event systems (DESs)
Dynamic models
Finite state machines
Hybrid systems
logistics
Marine vehicles
mathematical model
Monte Carlo simulation
predictive control
Predictive models
Quays
Resource management
Schedules
Scheduling
Seaports
Transport buildings, stations and terminals
Trucks
Vessels
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Description
Summary:We present a dynamical modeling of integrated (end-to-end) container terminal operations using finite state machine (FSM) framework where each state machine is represented by a discrete-event system (DES) formulation. The hybrid model incorporates the operations of quay cranes (QC), internal trucks (IT), and yard cranes (YC) and also the selection of storage positions in container yard (CY) and vessel bays. The QC and YC are connected by the IT in our models. As opposed to the commonly adapted modeling in container terminal operations, in which the entire information/inputs to the systems are known for a defined planning horizon, in this research we use real-time trucks, crane, and container storage operations information, which are always updated as the time evolves. The dynamical model shows that the predicted state variables closely follow the actual field data from a container terminal in Tanjung Priuk, Jakarta, Indonesia. Subsequently, using the integrated container terminal hybrid model, we proposed a model predictive algorithm (MPA) to obtain the near-optimal solution of the integrated terminal operations problem, namely the simultaneous allocation and scheduling of QC, IT, and YC, as well as selecting the storage location for the inbound and outbound containers in the CY and vessel. The numerical experiment based on the extensive Monte Carlo simulation and real dataset show that the MPA outperforms by 3-6% both of the policies currently implemented by the terminal operator and the state-of-the-art method from the current literature.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2021.3083598