Development of Optimization Model to Reduce Unloading and Loading Time at Berth in Container Ports

Mahpour, Alireza; Nazifi, Amin; Amiri, Amir Mohammadian

doi:10.1007/s40996-021-00590-2

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…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. Lin [34] et al optimized the berth allocation in container terminal by considering the service time and penalty cost.…”

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%

See 2 more Smart Citations

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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Section: Literature Review and Related Workmentioning

confidence: 99%

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

confidence: 99%

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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“…Escobar-Falcón et al [19] integrated the fuel consumption heterogeneous vehicle routing problem with two-dimensional loading constraints and presented a specialized genetic algorithm to solve the design of routes. Mahpour et al [20] determined the fitness function and the initial population and finally imposed constraints in the development process of the genetic algorithm (GA) to determine the optimal service time of container port berths. Avdagic et al [21] focused on use of the genetic algorithm for effectively narrowing the search space.…”

Section: Related Research On Emergencymentioning

confidence: 99%

Optimization of Port Emergency Materials Dispatch with Time Windows Constraints under Uncertainties

Wang

2021

Discrete Dynamics in Nature and Society

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Uncertainties exist and affect the actual port production. For example, at the beginning of 2020, the sudden outbreak of COVID-19 seriously affected terminal production and increased the short-term pressure of handling at container terminals. Consequently, a large number of containers were stacked at terminals, and the problem of terminal congestion became more serious. To solve the congestion problem of container terminals and ensure the priority dispatch of emergency materials, this study uses the optimized arrival patterns of external trucks and a priority dispatch strategy for emergency materials to establish a bilevel optimization model for container terminals and proposes a chaotic genetic algorithm based on logistic mapping as a solution. Through numerical experiments, the algorithm proposed in this study was compared with the genetic algorithm and adaptive genetic algorithm. The experimental results show that the model and algorithm proposed in this study can effectively reduce the total cost of containers in a terminal while ensuring the priority dispatch of emergency materials, reducing the overlapping part of the time window, optimizing the arrival mode of external trucks, and reducing the waiting time of external trucks, effectively alleviating the terminal congestion problem.

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“…us, ships can be directed to the optimal berth for maximal utility of the available port service capacity. Developing a multiple linear regression model, Mahpour et al [27] showed that access channel depths and the number of berths are the most significant contributing factors on the loading efficiency. Research on the airport gate assignment can be classified according to the optimization objective, i.e., to be passenger-oriented or agency-oriented [28].…”

Section: Introductionmentioning

confidence: 99%

Optimal Route Assignment at the Bus Hub with Multiple Berths for Minimal Passenger Transfer Distance

Zhang

Jin

Hao

et al. 2022

Journal of Mathematics

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Bus hub is characterized with multiple berths, each serving specific bus routes. When bus routes at different berths share the same stops en route, passengers to the shared stops may rush among these berths to catch the newly arriving bus, causing inconvenience and deteriorating bus service level. Thus, this research attempts to optimize bus route assignment to the berths at a bus hub to minimize passenger transfer distance among the optional berths. The problem is modeled with integer linear programming, with the constraints of bus service capacity. To enhance computation efficiency, exclusive and inclusive constraints based on the count of shared stops among the bus routes are additionally added to the original model, though they may bring gap from the optimal solution. Case study follows to apply the proposed set of models to a bus terminal, where a total of 26 routes are assigned to 11 berths. It is found that the models with additional constraints can greatly reduce calculation time at the cost of small or no gap from the optimal solution. Thus, the models with additional constraints are recommended to obtain ideal solution quickly. This research provides insights into bus route management at the bus terminal with multiple berths, contributing to enhanced passenger waiting experience.

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Development of Optimization Model to Reduce Unloading and Loading Time at Berth in Container Ports

Cited by 9 publications

References 23 publications

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

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

Optimization of Port Emergency Materials Dispatch with Time Windows Constraints under Uncertainties

Optimal Route Assignment at the Bus Hub with Multiple Berths for Minimal Passenger Transfer Distance

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