Scheduling of container-handling equipment during the loading process at an automated container terminal

Luo, Jiabin; Wu, Yue

doi:10.1016/j.cie.2020.106848

Cited by 58 publications

(25 citation statements)

References 38 publications

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“…Efficient scheduling of various types of equipment (i.e., different QCs, AYCs, and transport vehicles) is crucial to capture steady system performance of ACTs. In particular, the integrated scheduling problems of a container handling system have attracted much research attention [24,16,[25][26][27]. Moreover, the coordination of operations in ACTs was appropriately addressed in order to provide a complete schedule in an integrated way [28].…”

Section: Literature Reviewmentioning

confidence: 99%

Petri‐net‐based deadlock detection and recovery for control of interacting equipment in automated container terminals

Xing

Hao

et al. 2022

IET Intelligent Trans Sys

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In automated container terminals (ACTs), quay cranes (QCs), automated guided vehicles (AGVs), and automated yard cranes (AYCs) interact intensively to handle containers at seaside and yard side. This work investigates interacting equipment in ACTs that employ AGVs with the capability of lifting a container temporarily buffered at the transfer area in front of a storage block. By establishing and using the Petri net model of equipment interaction system (EIS) for container transportation, deadlock control problem is studied for handling operations in ACTs, where all QCs, AYCs, and transport vehicles are considered as system resources. Deadlock is characterized as maximal special circuits (MSCs) that are saturated at a system state. After a deadlock detection method through MSC enumeration in the system Petri net model is developed, a procedure is proposed to resolve deadlock situations where an AYC is involved in the corresponding circular waiting relations. By modifying the operation sequence of AYCs, the procedure can resolve the conflicts among concurrent processes so as to eliminate deadlocks. Examples are presented to illustrate the effectiveness of the deadlock handling method, which is also tested in a simulation study. Results show that the EIS can recover from detected deadlocks involving AYCs to ensure smooth transport operations of container jobs.

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Section: Literature Reviewmentioning

confidence: 99%

Petri‐net‐based deadlock detection and recovery for control of interacting equipment in automated container terminals

Xing

Hao

et al. 2022

IET Intelligent Trans Sys

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“…Given the fact that the loading and unloading process is an integrated process, the main part of this study has focused on the relationship between stacking strategies and the level of information about further transportation modes. A study conducted by Luo and Wu showed that the efficiency of transportation between the quayside and yard side might have a significant impact on the terminal's productivity [15]. Therefore, container terminal equipment should be operating as an integrated system to improve the terminal's performance.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A majority of them have focused on operational analysis [34], scheduling of container-handling equipment [15], and optimization of the container handling process considering equipment efficiency [35], while the present study tries to fill the gap between stacking strategies and overall equipment effectiveness by developing an agent-based Previous studies have dealt with container terminal efficiency and stacking strategies. A majority of them have focused on operational analysis [34], scheduling of containerhandling equipment [15], and optimization of the container handling process considering equipment efficiency [35], while the present study tries to fill the gap between stacking strategies and overall equipment effectiveness by developing an agent-based model to address the issues of container handling flow. Therefore, this study proposes different stacking strategy scenarios in which, in the base case, we don't have information about how the containers are handled further.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Uncertainty of ships' exact arrival time (in general, the planners of a container terminal can plan QCs/YCs worklist only a few hours prior to vessel arrivals) [15]; • Container terminal operators are unable to process further container transport modes (they don't know if the containers are going further with another deep-sea vessel, barge, rail, or road transport) [16]; • Most importantly, if they use more SCs at a peak time, there will be congestion of SCs [17].…”

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confidence: 99%

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Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach

Mazloumi

Hassel

2021

Sustainability

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Despite all the achievements in improving container terminal performance in terms of equipment and container stacking systems (CSS), terminal operators are still facing several challenges. One of these challenges is the lack of information about further transportation modes of the container, which leads to extra movements of the container inside the stacking area. Hence, we aimed to examine factors that affect container handling processes and to evaluate a container terminal’s overall equipment effectiveness. This study used data from a container terminal at the Port of Antwerp, Belgium. An agent-based model was developed based on a block-stacking strategy to investigate two scenarios: (1) having information about further transportation modes and (2) a base scenario. The Overall Equipment Effectiveness Index (OEE) was also adopted to evaluate the container terminal’s effectiveness in both scenarios. Results showed that having information on further transportation mode significantly increased the container outflow, and the OEE index improved compared to the base scenario’s results. Therefore, we recommend an integrated data-sharing system where all the stakeholders can share their information with no fear of losing their market share.

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“…On the basis of the above research, Zeng and Yang [ 12 ] proposed an integrated algorithm for the integrated scheduling problem with complex constraints, combining the genetic algorithm, simulation technology and neural network model. Luo and Wu [ 13 ] investigated an integrated scheduling model of AGVs and YCs during the loading process, aiming to minimize the ship’s berthing time. The B&B algorithm implemented by CPLEX and a proposed adaptive heuristic algorithm were used to solve small-sized problems and large-sized problems, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling of integrated scheduling problem of capacitated equipment systems with a multi-lane road network

Zhao

Qing-hua

et al. 2021

PLoS ONE

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The coordination of different container-handling equipment is an important method for improving the overall efficiency of automated container terminals. In the real terminal, we should consider many real-life issues, such as the equipment capacity, the equipment collision, changing lanes in the multi-lane road, and choosing one of container-handling lanes for each container. This paper proposes the integrated scheduling problem of three container-handling equipment with the capacity constraint and the dual-cycle strategy, for simultaneously solving the equipment scheduling problem, the assignment problem of the container-handling lane and the conflict-free route planning problem of automated guided vehicles (AGVs). With the objective of minimizing the ship’s berth time, we propose a mixed-integer programming model based on the space-time network representation method and two bilevel optimization algorithms based on conflict resolution rules. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model and two bilevel optimization algorithms.

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Scheduling of container-handling equipment during the loading process at an automated container terminal

Cited by 58 publications

References 38 publications

Petri‐net‐based deadlock detection and recovery for control of interacting equipment in automated container terminals

Petri‐net‐based deadlock detection and recovery for control of interacting equipment in automated container terminals

Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach

Modelling of integrated scheduling problem of capacitated equipment systems with a multi-lane road network

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