Dispatching Strategies of Drayage Trucks at Seaport Container Terminals with Truck Appointment System

Lange, Ann-Kathrin; Branding, Fredrik; Schwenzow, Tilmann; Zlotos, Constantin; Schwientek, Anne Kathrina; Jahn, Carlos

doi:10.1007/978-3-319-74225-0_21

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Port related road freight traffic can affect traffic flow dynamics on city roads. The ongoing growth of container ship sizes leads to high peak situations in landside container handling and thereby to a high traffic load on the port street network (Lange, et al, 2017). Delays on city roads may cause shippers to switch to competing rival ports; Wan et al (2013) determined that the increase in urban road congestion by 1% can cause from 0.90 to almost 2.50% decrease of container throughput.…”

Section: Literature Reviewmentioning

confidence: 99%

Improved port gate procedures for a better port-city relation

Zanne¹

2023

European Transport/Trasporti Europei

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Road congestion caused by port activities is a well-known problem that is often highlighted by local communities as one of the main negative issues related to port operations. Studies also show that road congestion can affect the competitive position of ports. The problem can be tackled in a number of ways. The paper is divided into two parts. In the first part of the paper, the authors analyse the literature on the effectiveness of various procedures and upgrades at the port gates that can improve the gate turnaround times. The second part is a case study. In the second part of the paper, the authors quantify the current negative impacts of port-related road congestion and the benefits of introducing selected measures at the gates of the port of Koper. Isolation of single best measure is impossible due to simultaneous introduction of measures.

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Section: Literature Reviewmentioning

confidence: 99%

Improved port gate procedures for a better port-city relation

Zanne¹

2023

European Transport/Trasporti Europei

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“…An agent-based simulation model was developed to assess the effectiveness of the proposed approach in minimizing the number of trucks with reservations that fail to arrive at the scheduled appointment. Lange et al [10] developed a discrete event simulation (DES) model to investigate various time window selection strategies for port drayage companies. The study considered factors such as company sizes and the strategies employed by competitors.…”

Section: Classification Based On the Modeling Approachmentioning

confidence: 99%

“…The number of yard cranes (h it ) required to satisfy the workload (w it ) can be calculated from Equation (10) [29].…”

mentioning

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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