Scheduling multiple yard cranes in two adjacent container blocks with position-dependent processing times

He, Junkai; Zheng, Feifeng; Liu, Ming

doi:10.1016/j.cie.2019.07.013

Cited by 27 publications

(7 citation statements)

References 29 publications

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“…Iris et al [3] presented an adaptive large-neighborhoodbased heuristic framework to solve the weekly berth and quay crane assignment problem. References [4][5][6] studied the YC scheduling problem, and Chu et al [4] studied the management of three yard cranes in two adjacent container blocks in line. Gharehgozli et al [5] researched the problems of both stacking and lifting tasks in a container yard.…”

Section: Literature Reviewmentioning

confidence: 99%

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An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

Chen,

Liu

2024

JMSE

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In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an RYACT, this study examines the “RYACT–train” cooperative optimization problem in the mode of “unloading before loading” for train containers. A mixed-integer programming model with the objective of minimizing the maximum completion time of automated rail-mounted gantry crane (ARMG) tasks is established. An adaptive large neighborhood search (ALNS) algorithm and random search algorithm (RSA) are designed to solve the abovementioned problem, and the feasibility of the model and algorithm is verified by experiments. At the same time, the target value and calculation time of the model and algorithms are compared. The experimental results show that the model and the proposed algorithms are feasible and can effectively solve the “RYACT–train” cooperative optimization problem. The model only obtains the optimal solution of the “RYACT–train” cooperative scheduling problem with no more than 50 tasks within a limited time, and the ALNS algorithm can solve examples of various scales within a reasonable amount of time. The target value of the ALNS solution is smaller than that of the RSA solution.

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Section: Literature Reviewmentioning

confidence: 99%

“…(3) The horizontal moving speed of ARMG carts remains unchanged. (4) In the RYACT (or train), the operation time required for an ARMG to g is equal to that required to release a container.…”

Section: Assumptionmentioning

confidence: 99%

An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

Chen,

Liu

2024

JMSE

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“…Zhou et al [16] and Iris et al [17] reviewed AGV use in green ports. Several studies [18][19][20][21][22][23] have focused on reducing the operation time and waiting time of AGVs. Other studies [24][25][26] have investigated YC scheduling rules and travel paths.…”

Section: Scheduling Study Of Agvs and Ycs In Automated Container Term...mentioning

confidence: 99%

“…Equation (18) establishes the relationship between the moment when the spreader of RGC r moves above the AGV operation lane and when RGC r starts interacting with the AGV in the operation task i. Equation (19) represents the end moment of task i. Equation (20) corresponds to the scenario when a ship's arrival is delayed, requiring temporary storage of the train-ship task i in the corresponding bay b of the temporary storage area.…”

Section: Utilization Rate Of Agv T Use F Ulmentioning

confidence: 99%

Research on the Multi-Equipment Cooperative Scheduling Method of Sea-Rail Automated Container Terminals under the Loading and Unloading Mode

Yang,

Sun,

et al. 2023

JMSE

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A sea-rail automated container terminal (SRACT) plays a crucial role in the global logistics network, combining the benefits of sea and railway transportation. However, addressing the challenges of multi-equipment cooperative scheduling in terminal and railway operation areas is essential to ensure efficient container transportation. For the first time, this study addresses the cooperative scheduling challenges among railway gantry cranes, yard cranes, and automated guided vehicles (AGVs) under the loading and unloading mode in SRACTs, ensuring efficient container transportation. This requires the development of a practical scheduling model and algorithm. In this study, a mixed integer programming model was established for the first time to study the multi-equipment cooperative scheduling problem of a SRACT under the loading and unloading mode. A self-adaptive chaotic genetic algorithm was designed to solve the model, and the practicability and effectiveness of the model and algorithm were verified by simulation experiments. Furthermore, this study also proposes an AGV number adjustment strategy to accommodate changes in vessel arrival delays and train container types. Simulation experiments demonstrated that this strategy significantly reduces loading and unloading time, decreases equipment energy consumption, and improves the utilization rate of AGVs. This research provides valuable guidance for ongoing SRACT projects and advances and methodological approaches in multi-equipment co-operative scheduling for such terminals.

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“…A crane is an important type of logistics equipment to realize material handling mechanization in factory workshops or warehouses, railway freight yards, port wharfs, and other locations [1,2]. Three phase AC (alternating current) asynchronous motors (hereinafter referred to as motors) serve as the main power devices for a crane's cart running mechanism, trolley running mechanism, and spout lifting mechanism [3,4].…”

Section: Introductionmentioning

confidence: 99%

Research on the Hoisting Motor Drive System’s Active Disturbance Rejection Control and Energy Consumption for a Crane

Zhong

Ma²,

Hao

et al. 2021

IEEE Access

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To allow the hoisting motor drive system of a crane to track a load torque quickly, a linearization method was used to transform a motor nominal dynamics model into two decoupled linear rotor speed and flux linkage subsystems. The method based on the theory of differential geometry was a precise feedback method. Two active disturbance rejection controllers (ADRCs) with identical structures were designed for the rotor speed and flux linkage subsystems. The extended state observer of the ADRC could estimate the unmodeled dynamics of the motor, the variation of motor parameters due to heating, and the unknown disturbances of the motor system to determine the total disturbances of the system. A closed-loop system with ADRC and an open-loop system were compared. The motor's full-load starting time was reduced by about 50%. When the motor operated smoothly at different load rates and the rated load was suddenly applied, the electromagnetic torque fluctuation range did not exceed 20 N• m. The rotor flux was always stable at the reference value. The motor speed decreased, but the amount of decrease did not exceed 7 rad/s. The closed-loop system had a significant energy-saving effect during the motor's starting process. The power saving rate was about 55%-59% if the motor started with a light load. The power saving rate could reach 71% if the motor started with a heavy load. The ADRC system could accurately estimate the unknown model of the rotor speed and flux linkage subsystems, and adapt to parameter variations of the motor stator and rotor resistance in the range of ±10%. Motor: Te, TL Electromagnetic and load torques. TN Nominal torque. ET Electromagnetic torque tracking error. np Motor's pole logarithm. Je Rotational inertia of the rotor. n Rotor speed. ω Electric angular velocity. ωr Mechanical angular velocity. α, β Static two-phase coordinate axis.

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Scheduling multiple yard cranes in two adjacent container blocks with position-dependent processing times

Cited by 27 publications

References 29 publications

An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

Research on the Multi-Equipment Cooperative Scheduling Method of Sea-Rail Automated Container Terminals under the Loading and Unloading Mode

Research on the Hoisting Motor Drive System’s Active Disturbance Rejection Control and Energy Consumption for a Crane

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