Truck Arrival Management At Maritime Container Terminals

2016 ◽  
Author(s):  
Daniela Ambrosino ◽  
Lorenzo Peirano
Keyword(s):  
Container Terminals ◽  
Truck Arrival

scholarly journals Integrating truck arrival management into tactical operation planning at container terminals

2013 ◽  
Vol 20 (Special-Issue) ◽  
pp. 32-46 ◽  
Author(s):  
Zhong-Zhen Yang ◽  
Gang Chen ◽  
Dong-Ping Song
Keyword(s):  
Integrated Model ◽  
Container Terminals ◽  
Computational Time ◽  
Planning Model ◽  
Sequential Model ◽  
Terminal Performance ◽  
Planning Models ◽  
Gate Congestion ◽  
Terminal Operations ◽  
Truck Arrival

Abstract Truck arrival management (TAM) has been recognized as an effective solution to alleviate the gate congestion at container terminals. To further utilize TAM in improving the overall terminal performance, this study integrates TAM with the other terminal operations at a tactical level. An integrated planning model and a sequential planning model are presented to coordinate the major terminal planning activities, including quayside berth allocation, yard storage space allocation and TAM. A heuristic-based genetic algorithm is developed to solve the models. A range of numerical examinations are performed to compare two planning models. The result shows that: the integrated model can improve the terminal performance significantly from the sequential model alone, particularly when the gate capacity and the yard capacity are relatively low; whereas the sequential model is more efficient than the integrated model in terms of computational time.

scholarly journals Reshuffle minimisation to improve storage yard operations efficiency

2021 ◽  
Vol 15 ◽  
pp. 174830262199401
Author(s):  
Hammed Bisira ◽  
Abdellah Salhi
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Heuristic Approach ◽  
Container Terminals ◽  
Exact Method ◽  
Computational Results ◽  
Binary Integer Programming ◽  
Integer Programming Model ◽  
Compatibility Test ◽  
Storage Area

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory.

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