A Flexible Scheduling for Twin Yard Cranes at Container Terminals Considering Dynamic Cut-Off Time

Li, Junjun; Yang, Jingyu; Xu, Baoyun; Yin, Wenjun; Yang, Yongsheng; Wu, Jerry J.; Zhou, Ye; Shen, Yi

doi:10.3390/jmse10050675

Cited by 8 publications

(6 citation statements)

References 19 publications

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“…Equation (1) indicates that a task can only be operated by a one-YC and only once. Equation (2) shows the equal constraints of task working time, YC walking time, and loading and unloading time. Equation (3) indicates that the completion time of the i th task of YC n is the sum of the corresponding container truck's arrival and working times.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Among the existing literature on YC scheduling, Li et al, 2022 [2] developed a YC scheduling model considering no crossing constraints and dynamic deadlines. To improve the flexibility of container yard handling, a joint scheduling method (LRPSO) based on particle swarm optimization and local rescheduling strategy is proposed to solve the problem faster and more efficiently.…”

Section: Introductionmentioning

confidence: 99%

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Yard Crane Rescheduling under the Influence of Random Fault

et al. 2023

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In the operation of the imported container area of the container yard, the fault of the yard crane often occurs, and the fault is random and unpredictable, which greatly affects the operational efficiency of the container yard. To improve the operation efficiency of the container yard, this paper studies the rescheduling optimization problem of the multi-container area and multi-yard crane when random faults occur in container lifting operations in the container import area. Considering the different impacts of different fault conditions on the container yard operation, the fault impact judgment mechanism is established. The waiting time of external container trucks and customer satisfaction is considered for yard crane rescheduling. Yard crane rescheduling model after the fault is constructed, aiming at the minimum deviation from the original scheduling scheme. And the AEA (annealing evolution algorithm) algorithm is used to solve it. The effectiveness of magic and the specificity of the algorithm are verified by the analysis of numerical examples in different scales. The research data of Dalian Port is used to carry out experiments, and the experimental analysis of examples in different scales verifies the effectiveness of the model and the scientific nature of the algorithm. Compared with the existing scheme, this scheme is more practical, which can not only give the treatment scheme immediately when the fault occurs but also effectively improve the working efficiency of the container yard and provide a reference for the port to enhance customer satisfaction.

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Yard Crane Rescheduling under the Influence of Random Fault

et al. 2023

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“…The Problem Objective Function (Minimize) Model Algorithm [11] Twin-crane Interference-free -- [16] Twin-crane Makespan MILP Heuristic [21] Crane + YT Makespan MILP BD [14] AGV + ASC Makespan MCF B and B [13] Twin-crane Makespan MILP ALNS [17] Twin-ASC Makespan MILP GA [22] Multi-crane Delay time + Energy consumption MILP GA + PSO [18] Crane + YT Makespan Analytical GA + PSO [15] Twin-crane Makespan MILP GA + Greedy [3] SM + Crane Crane's movements cost + Penalty cost MIP B and B + CG [23] Crane + YT Makespan MILP DP [4] QC + AGV + Crane Berthing time CP Heuristic [24] Twin-crane Makespan MILP PSO [25] ASC + AGV Makespan MILP GA [26] Twin-crane Makespan MILP Heuristic + DP [2] Dual-ASC Makespan MILP NS [27] Twin-crane ASC and truck waiting time MILP Look-Ahead [20] Twin…”

Section: Literaturementioning

confidence: 99%

“…The degree constraint (23) imposes that exactly two edges are incident into each vertex associated with a task. In Constraint (24), the operation sequence constraint of ASCs is converted into the well-known generalized sub-tour elimination constraints. However, Constraint (24) has a cardinality growing exponentially with N. Therefore, we relax the constraints containing binary variables u ij ∈ {0, 1} to variables 0 ≤ u ij ≤ 1, namely, Constraint (26).…”

Section: A Lower Boundmentioning

confidence: 99%

An Iterative Re-Optimization Framework for the Dynamic Scheduling of Crossover Yard Cranes with Uncertain Delivery Sequences

Wang

2023

JMSE

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In yard-crane scheduling problems, as loading operations take priority over unloading, the delivery sequence of unloading from the quaysides to the yard is uncertain. The delivery sequence changes may make crane scheduling more difficult. As a result, the crane operations schedules developed statically become suboptimal or even infeasible. In this paper, we propose a dynamic scheduling problem considering uncertain delivery sequences. A mixed-integer linear program is developed to assign tasks to cranes and minimize the makespan of crane operations. We propose an iterative solution framework in which the schedules are re-optimized whenever the delivery sequence change is revealed. A genetic algorithm is proposed to solve the problem, and a greedy algorithm is designed to re-optimize and update the solution. To make the updated solution take effect as soon as possible, regarding batch-based task assignment, the tasks in the scheduling period are divided into several batches. In this case, the instant requests arising from the delivery sequence change are added to corresponding batch tasks and re-optimized together with the tasks of this batch. In addition, a relaxation model is formulated to derive a lower bound for demonstrating the performance of the proposed algorithm. Experimental results show that the average gap between the algorithm and the lower bound does not exceed 5%. The greedy insertion algorithm can re-optimize the instant requests in time. Therefore, the proposed iterative re-optimization framework is feasible and has the advantages (necessity) of batch-based task assignment.

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“…Li et al [21] developed a novel twin-yard crane scheduling model that incorporates two critical elements: the no-crossing constraints and the dynamic cut-off time. This model aims to enhance container yard operations' flexibility and boost terminal yards' overall efficiency.…”

Section: Yard Crane Schedulingmentioning

confidence: 99%

A Multi-Stage Approach for External Trucks and Yard Cranes Scheduling with CO2 Emissions Considerations in Container Terminals

Talaat,

Gheith,

Eltawil

2023

Logistics

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Background: In container terminals, optimizing the scheduling of external trucks and yard cranes is crucial as it directly impacts the truck turnaround time, which is one of the most critical performance measures. Furthermore, proper scheduling of external trucks contributes to reducing CO2 emissions. Methods: This paper proposes a new approach based on a mixed integer programming model to schedule external trucks and yard cranes with the objective of minimizing CO2 emissions and reducing truck turnaround time, the gap between trucking companies’ preferred arrival time and appointed time, and the energy consumption of yard cranes. The proposed approach combines data analysis and operations research techniques. Specifically, it employs a K-means clustering algorithm to reduce the number of necessary truck trips for container handling. Additionally, a two-stage mathematical model is applied. The first stage employs a bi-objective mathematical model to plan the arrival of external trucks at the terminal gates. The second stage involves a mathematical model that schedules yard cranes’ movements between different yard blocks. Results: The results show that implementing this methodology in a hypothetical case study may lead to a substantial daily reduction of approximately 31% in CO2 emissions. Additionally, the results provide valuable insights into the trade-off between satisfying the trucking companies’ preferred arrival time and the total turnaround time. Conclusions: The integration of data clustering with mathematical modeling demonstrates a notable reduction in emissions, underscoring the viability of this strategy in promoting sustainability in port-related activities.

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A Flexible Scheduling for Twin Yard Cranes at Container Terminals Considering Dynamic Cut-Off Time

Cited by 8 publications

References 19 publications

Yard Crane Rescheduling under the Influence of Random Fault

Yard Crane Rescheduling under the Influence of Random Fault

An Iterative Re-Optimization Framework for the Dynamic Scheduling of Crossover Yard Cranes with Uncertain Delivery Sequences

A Multi-Stage Approach for External Trucks and Yard Cranes Scheduling with CO2 Emissions Considerations in Container Terminals

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