Maritime Transport Research最新文献

The circular economy (CE) brings many opportunities, but also many challenges for ports, cities, and their hinterland. The goal of this paper is twofold. First, we embrace the inherent uncertainty of the spatial impact of the CE on ports and cities. We employ scenario methodology to guide us in steering this uncertainty by developing four scenarios. To explore the complexity of these four scenarios, we focus on the Dutch province of South-Holland. This region hosts the port of Rotterdam, the largest port in Europe, and its direct hinterland consists of a dense urbanised region. As such, the four scenarios cannot only shed a light on the future of the port, but also how its relations with its direct urbanized hinterland can potentially change. In two scenarios deglobalisation occurs. The consequences are, on the one hand, that the port's focus changes more to its direct hinterland instead of a global oriented focus. On the other hand, the existing water bound industrial areas in, or nearby cities increase in importance, in contrast to the contemporary pressure to redevelop these into waterfront residential and commercial areas. In other words, port and city/region grow towards each other. The second goal of the paper is to dive into the specific consequences of these scenarios for day-to-day planning practices. By combining micro-economic and AIS shipping data, we discovered the most important terminals and industrial areas for the transition towards a CE in port, city, and hinterland.

This paper contributes to the literature by deriving upper and lower bounds on the fuel consumption in container shipping. The bounds are derived from sailing distances, port times, and the possible arrival times at ports/ the berth windows negotiated between the ocean carrier and the port operators. Crucially, the derived bounds can be used in conjunction with any of the common fuel consumption functions proposed in the literature. This latter is especially important since currently there is no consensus on a specific functional form for the fuel consumption function. The behavior of the bounds will be illustrated with numerical examples.

This study addresses the pressing need for the Norwegian fishery sector to align with national reduction targets and mitigate its environmental impact. Norway has committed to reducing GHG emissions from the fishery sector by at least 40% by 2030 and 95% by 2050. We propose a mathematical model designed for the strategic renewal of the Norwegian fishing fleet by introducing low- and zero-emission propulsion systems. This model generates fleet renewal schedules that minimize the total operational and renewal costs while ensuring compliance with emission targets. We apply our model to a case study based on the Norwegian fishing fleet and determine the optimal decarbonization strategy. We then analyze the impact of changes in energy costs and emission taxes on this strategy through a sensitivity analysis Our results indicate that (1) fleet renewal is mainly driven by the emission reduction targets, rather than economic benefits, and (2) zero-emission propulsion systems are preferable to low-emission propulsion systems when decarbonizing the fleet.

In a container terminal, the length of time that containers remain in the yard, known as Container Dwell Time (CDT), is considered one of the significant operational indicators due to its direct correlation with terminal productivity and efficiency. However, due to complex processing procedure and the involvement of various logistics stakeholders, CDT is subject to high uncertainty, making it more difficult for the terminal to manage. To address this issue, this paper presents a comprehensive framework to identify the Key Factors (KFs) influencing prolongation of CDT for import containers. In order to elucidate abnormal cases from dataset which contains yard loading information, the Process Mining (PM) method is utilized. Subsequently, XAI has been utilized to identify the KFs of import CDT. To reflect reality as closely as possible, we collected event data from a container terminal in Busan, Korea. Based on experiments, the KFs thus identified were: 1) Temperature, 2) Weight of container, 3) Voyage number of container 4) Block, 5) Shipping company, and 6) Month of discharging. To conclude, we formulated domain knowledge-based interpretations of the six most influential KFs.

We study the potential effects of introducing autonomous ferries in a transportation system of water buses. We develop two integer linear programming models and a heuristic to find weekly passenger transportation plans. One model is tailored for a fleet of autonomous ferries and the other one for manually operated ferries. The objective of the models is to minimize a penalty function for unmet demand, adding up penalties on time delays with respect to the wished time of arrivals of the passengers and penalties on the assignment of passengers to alternative transportation modes. The models differ because working laws affect the crews’ working capacities, and we study the changes when these requirements are absent with autonomous ferries. Our work is motivated by the case of Bergen, a coastal city in Norway. In this case, the use of autonomous ferries has the potential to improve passengers’ utility significantly. However, we suggest that it may be beneficial to consider autonomous ferries as a complementary alternative that can operate especially in low-demand hours—a recommendation that may be particularly relevant if there are few autonomous ferries available or the ferries can only be operative for a limited number of hours of the day.