Optimal berth allocation, time-variant quay crane assignment and scheduling with crane setups in container terminals

2016 ◽  
Vol 254 (3) ◽  
pp. 985-1001 ◽  
Author(s):  
Yavuz B. Türkoğulları ◽  
Z. Caner Taşkın ◽  
Necati Aras ◽  
İ. Kuban Altınel
Author(s):  
Abbas Al-Refaie ◽  
Hala Abedalqader

This research proposes two optimization models to deal with the berth allocation problem. The first model considers the berth allocation problem under regular vessel arrivals to minimize the flow time of vessels in the marine container terminal, minimize the tardiness penalty costs, and maximize the satisfaction level of vessels’ operators on preferred times of departure. The second model optimizes the berth allocation problem under emergency conditions by maximizing the number of assigned vessels, minimizing the vessel’s waiting time, and maximizing the satisfaction level on the served ships. Two real examples are provided for model illustration under regular and emergent vessel arrivals. Results show that the proposed models effectively provide optimal vessel scheduling in the terminal, reduce costs at an acceptable satisfaction level of vessels’ operators, decrease the waiting time of vessels, and shorten the delay in departures under both regular and emergent vessel arrivals. In conclusion, the proposed models may provide valuable assistance to decision-makers in marine container terminals on determining optimal berth allocation under daily and emergency vessel arrivals. Future research considers quay crane assignment and scheduling problems.


2019 ◽  
Vol 11 (7) ◽  
pp. 2018 ◽  
Author(s):  
Hsien-Pin Hsu ◽  
Tai-Lin Chiang ◽  
Chia-Nan Wang ◽  
Hsin-Pin Fu ◽  
Chien-Chang Chou

Container terminals help countries to sustain their economic development. Improving the operational efficiency in a container terminal is important. In past research, genetic algorithms (GAs) have been widely used to cope with seaside operational problems, including the berth allocation problem (BAP) and quay crane assignment problem (QCAP) individually or simultaneously. However, most GA approaches in past studies were dedicated to generate time-invariant QC assignment that does not adjust QCs assigned to a ship. This may underutilize available QC capacity. In this research, three hybrid GAs (HGAs) have been proposed to deal with the dynamic and discrete BAP (DDBAP) and the dynamic QCAP (DQCAP) simultaneously. The three HGAs supports variable QC assignment in which QCs assigned to a ship can be further adjusted. The three HGAs employ the same crossover operator but a different mutation operator and a two-stage procedure is used. In the first stage, these HGAs can generate a BAP solution and a QCAP solution that is time-invariant. The time-invariant QC assignment solution is then further transformed into a variable one in the second stage. Experiments have been conducted to investigate the effects of the three HGA and the results showed that these HGAs outperformed traditional GAs in terms of fitness value. In particular, the HGA3 with Thoros mutation operator had the best performance.


2014 ◽  
Vol 235 (1) ◽  
pp. 88-101 ◽  
Author(s):  
Yavuz B. Türkoğulları ◽  
Z. Caner Taşkın ◽  
Necati Aras ◽  
İ. Kuban Altınel

2020 ◽  
Vol 12 (8) ◽  
pp. 3202 ◽  
Author(s):  
Ahmed Karam ◽  
Amr Eltawil ◽  
Kristian Hegner Reinau

Despite a significant number of studies that have focused on the operational efficiency of container terminals, existing literature has paid little attention to improving energy efficiency, e.g., energy consumption and negative externalities in container terminals. Most researchers consider energy-saving goals when allocating berths and quay cranes to vessels, assuming that internal trucks are in sufficient supply. Furthermore, recent studies have revealed that shortage of internal trucks has become an issue that greatly affects the operational and energy efficiencies of container terminals. This work presents a planning model that integrates berth allocation, quay crane assignment, and internal truck assignment problems. The developed model contributes to existing literature by including energy-saving goals in the integrated planning of these problems, as well as including important realistic factors such as shortages of internal trucks and handling time estimations, thus producing a reliable handling plan that achieves energy and cost savings without additional truck investment. To solve realistic problems, a Lagrangian relaxation-based method is developed. Furthermore, the benefits of the developed approach are demonstrated by comparing it to an existing approach. On average, our approach could improve the solutions of the integrated problem with different numbers of internal trucks by 6% compared to the solutions obtained using the existing approach.


2014 ◽  
Vol 587-589 ◽  
pp. 1785-1788
Author(s):  
Zhi Jun Gao ◽  
Chun Ji Wu ◽  
Qing Yu Zhao ◽  
Jin Xin Cao

The major difficulties of the operation of loading, unloading and transportation at container terminals are how to schedule berths, quay cranes and trucks more effectively and efficiently. Therefore, how to optimize their configurations effectively and connect them more reasonably is a problem which should be solved eagerly. However, a reasonable and effective optimization model is the basis and the key of this problem. The operation time of container terminals mainly depends on the time of ships in port and the operation time of trucks, quay cranes and yard cranes. So, the objective of this paper is to minimize the sum of these four parts. An optimization model based on some reasonable and necessary hypotheses is proposed and an algorithm and procedure are designed.


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