Optimal berth allocation under regular and emergent vessel arrivals

Al–Refaie, Abbas; Abedalqader, Hala

doi:10.1177/1475090220937888

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…De et al [4] incorporated fuel consumption cost into the dynamic berth allocation problem and designed a chemical reaction optimization approach to solve it. Al-Refaie and Abedalqader [5] studied the berth allocation problem and proposed two optimization models under regular vessel arrivals and under emergency conditions, separately. Wawrzyniak et al [6] investigated the algorithm selection problem for solving the berth allocation problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Terminal Berth and Quay Crane Joint Scheduling in Container Ports Considering Carbon Cost

et al. 2023

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As container ports become increasingly important to the global supply chain, a growing number of ports are improving their competencies by consolidating multiple terminal resources internally. In addition, in the context of energy conservation and emission reduction, ports measure competitiveness not only in terms of terminal size, throughput and service level, but also in terms of low energy consumption and low pollution. Therefore, a nonlinear mixed-integer programming model considering the cost of carbon is developed for the multi-terminal berth and quay crane joint robust scheduling problem under uncertain environments to minimize the sum of expectation and variance of total cost under all randomly generated samples. The model considers the water depth and interference of quay cranes, etc. The expected vessel arrival time and the average operational efficiency plus relaxation are used as their actual values when scheduling. Finally, an improved adaptive genetic algorithm is developed by combining the simulated annealing mechanism, and numerical experiments are designed. The results show that the joint berth and quay crane scheduling with uncertainties and a multi-terminal coordination mechanism can effectively reduce the operating cost, including carbon costs and the vessel departure delay rate, and can improve resource utilization. Meanwhile, the scheduling with the multi-terminal coordination mechanism can obtain more significant improvement effects than the scheduling with uncertainties.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-Terminal Berth and Quay Crane Joint Scheduling in Container Ports Considering Carbon Cost

et al. 2023

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“…Tan [31] et al integrated the berth allocation problem and quay crane assignment problem to minimize the time of waiting and delay departure. Al-Refaie and Abedalqader [32] considered continuous berth scheduling problem and proposed two models that mainly aimed to reduce terminal operating costs and improve terminal operation efficiency. Mahpour [33] et al analyzed several factors affecting terminal operation and obtained the best time to serve vessels.…”

Section: Literature Review and Related Workmentioning

confidence: 99%

“…Constraint (31) ensures that the total blocks occupied by each vessel in the export empty container storage yard do not exceed the upper and lower limits it can take up. Constraints (32) and (33)…”

Section: Model Formulation Of Berth and Yard Integrated Scheduling With Synchronous Decision Time Tickmentioning

confidence: 99%

“…e objective about total time consumption for liners consists of three subobjectives, which are the time of waiting time for berth, the berthing time at the terminal, and the handling time. e 20 6,7,9,10,11,12,13,15,17,21 VI 3,6,7,10,11,13,14,15,19,22,23,24,25,28,29,30,33,40,41,47,54,55,56,57,60 1,3,4,5,8,9,11,12,17,20,25,31,32,33,34,35,40,…”

Section: Multiobjective Solution Pareto Analysismentioning

confidence: 99%

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Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Jiang

Lei

2022

Discrete Dynamics in Nature and Society

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Container terminal operators have practical and clear requirements on improving operational efficiency and service level to address running challenges. The resource allocation and collaborative scheduling of quayside berth and storage yard are vital issues in the optimization of container terminal handling systems (CTHSs). The allocation of berth in quayside and blocks on storage yard directly affects the running efficiency of CTHS. Consequently, we focus on the berth and yard collaborative allocation for import and export synchronous operations (BYCA-IESOs) and propose the BYCA-IESO research model based on synchronous or asynchronous integrated scheduling strategy by computational logistics. The BYCA-IESO model is a mixed integer quadratic programming model to minimize multiple time consumption of calling liners and the total horizontal transferring distances of yard trailers at container terminals. Furthermore, we design other two allocation policies for comparison on the BYCA-IESO, which are both multistage scheduling strategy profiles. CPLEX 20.1.0 is applied to implement and solve the model and tactics of BYCA-IESO. Accordingly, the feasibility, validity, and relative merits of the models and strategies are obtained and verified by analyzing and comparing multiple numerical experimental results.

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“…Trade globalization has promoted the vigorous development of the shipping industry, but followed by the problem of waterway and port dredging. [1][2][3][4] Cutter suction dredger is a kind of dredger widely used in dredging engineering, which has the advantages of high construction efficiency and low comprehensive cost. 5,6 With the increase of equipment excavation capacity and haul distance, it is more widely used in dredging and hydraulic reclamation construction.…”

Section: Introductionmentioning

confidence: 99%

Productivity regression analysis of cutter suction dredger considering operating characteristics and equipment status

Shang

Tian³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

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In order to optimize the operation parameters of cutter suction dredger in real time and adjust productivity as needed, a construction optimization strategy based on real-time productivity regression analysis is proposed. Machine learning methods, including Support Vector Regression (SVR), Gradient Boosting Regression Tree (GBRT), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and a Super Learner that made up of them, are used to mine relevant features based on the big data of operation characteristics and equipment status. Firstly, the working principle of cutter suction dredger is analyzed, the features that need real-time monitoring are determined, and the above features are classified. Then, some missing values and outliers in the data are deleted. Next, Lasso method is used to eliminate the variables that are not related to the regression target, and the redundant variables are combined. In addition, five machine learning methods are used to train and test the off-line productivity data of cutter suction dredger. And they are used to fit recent online productivity data. Super Learner performed best, which achieved the highest R2 (0.917), the lowest RMSE (75.096) and MAE (61.422) in the five models for online regression. Furthermore, the calculation time of each model is discussed, and the feasibility of the method proposed in this study for real-time regression of online productivity data has been confirmed. Finally, the importance of characteristics is analyzed to provide guidance for dredging operations under restricted construction conditions. According to the regression results and the importance of features, operators can give priority to adjusting some features to adjust the real-time construction productivity of dredger.

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Optimal berth allocation under regular and emergent vessel arrivals

Cited by 7 publications

References 17 publications

Multi-Terminal Berth and Quay Crane Joint Scheduling in Container Ports Considering Carbon Cost

Multi-Terminal Berth and Quay Crane Joint Scheduling in Container Ports Considering Carbon Cost

Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Productivity regression analysis of cutter suction dredger considering operating characteristics and equipment status

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