Benchmarking the energy efficiency of ships is not a straightforward task, mainly due to the diversity of operations. Although driving cycles have been used for decades in evaluating the performance of road vehicles, these do not exist in formal policy-making for maritime transport. This work builds on a previously proposed methodology. It uses noon reports of 327 vessels for 2019 to construct operational cycles for seven size classes of container ships using the main engine power as the main parameter. Concerning the main engine emissions, the resulting cycles reduce variation in the carbon intensity indicator values by more than 30% while maintaining an average accuracy of 97.7% in absolute emissions. These figures show that the concept can improve operational carbon intensity indicators in terms of robustness and their technical counterparts in optimizing ship design. The paper also proposes further work required for benchmarking applications in policy-making.
The decarbonisation of shipping has become a high priority on the environmental and political agenda. The prospect of implementing an Emissions Trading System (ETS) for shipping has come to prominence as a proposed mechanism for speeding up the decarbonisation of the industry, with the EU taking proactive action to include shipping within the EU ETS by 2023. This paper analyses and provides a qualitative review of the historical development of the discussions and actions taken at both global level (by the International Maritime Organization (IMO)) and at regional level within the EU. A SWOT analysis of the potential implementation of an ETS for shipping is then presented. The paper concludes that an ETS for shipping can incentivise greater investment in, and deployment of, green technologies that will have the effect of reducing the carbon footprint of the shipping industry. However, the speed and significance of this effect will depend upon the specific shipping market segment and the relative stage in shipping market cycles over time. It is further concluded that despite the imminent unilateral introduction of shipping into the EU ETS, it is important that the IMO continues its work to develop a global ETS that promotes a ‘level playing field’ for competition within the sector and eliminates the risk of carbon leakage.
In this article, the author describes how the creation of the Danish maritime museums in 1915 and 2013 – both generously funded by maritime foundations and actors – was perceived by the shipping industry as initiatives that would help market the industry in the eyes of the public. He argues more generally that national maritime museums constitute focal points for disseminating narratives that legitimate maritime activities and establish these activities as symbols of national identities. It is suggested that maritime historians, curators and scholars reflect on the relationship between maritime industry actors and museum exhibition narratives, and consider the interests and capital that potentially underpin museums’ and curators’ decisions.
Ship engines are subject to a very demanding work environment, where maximum availability is a must. In this project we look at different operational variables of a marine engine from large cargo ships, with the aim of detecting and trending damage onset on different engine sub-components. This information can be used by owners to expedite O&M interventions and maximize ship availability.
Manufacturing companies who ship goods globally often rely on external Logistics Service Providers (LSPs) to manage the containerization and transportation of their freight. Those LSPs are usually required to follow rules when deciding how to mix the goods in the containers, which complicates the planning task. In this paper, we study such a freight containerization problem with a specific type of cargo mixing requirements recurrently faced by an international LSP. We show that this problem can be formulated as a Multi-Class Constrained Variable Size Bin Packing Problem: given a set of items that all have a size and a fixed number of classes for which they can take certain values, the objective is to pack the items in a minimum-cost set of bins while ensuring that the size capacity and maximum number of distinct values per class are not exceeded in any of the bins. We propose two adapted and one novel greedy heuristics, as well as an Adaptive Large Neighborhood Search (ALNS) metaheuristic, to find feasible solutions to the problem. We also provide a pattern-based formulation that is used to obtain lower bounds using a Column Generation approach. Using three extensive datasets, including a novel one with up to 1000 items and 5 classes reflecting real industrial cases, we show that the novel greedy heuristic outperforms the adaptations of the existing ones and that our ALNS yields significantly better solutions than a commercial solver within a mandatory 5-minute time limit. Practical insights are given about the solutions for the industrial benchmark.
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Roll-on roll-off (RoRo) shipping plays an important role in freight transport on the European continent, and is faced with the challenge of reducing its CO2 emissions while increasing its efficiency. Dual cycling, in which loading and discharging processes are carried out simultaneously, achieves this goal by reducing the turnaround time of vessels in port and thus the CO2 output of handling equipment in port and fuel consumption through slow steaming at sea. Optimizing the dual cycling operations on RoRo vessels has not yet been investigated in the literature. This paper presents the novel RoRo dual cycling problem (RRDCP), and formulates it using integer programming (IP) with the objective to minimize the total makespan of discharging and loading operations. We further prove that the RRDCP is NP-complete by a reduction from a general machine scheduling problem, and introduce a novel heuristic to solve the problem called a generalized random key algorithm (GRKA). We evaluate the IP model and GRKA approach on both generated and industrial instances, showing that the GRKA heuristic finds optimal or near-optimal solutions to real-world problems in just seconds. We provide managerial insights on industrial instances, which indicate that our approach leads to a reduction in fuel consumption and CO2 emissions of up to 25% for RoRo operations.
Ship designers face increasing pressure to comply with global emission reduction ambitions. Alternative fuels, potentially derived from bio-feedstock or renewable electricity, provide promising solutions to this problem. The main challenge is to identify a suitable ship power system, given not only uncertain emission requirements but also uncertain fuel and carbon emission prices. We develop a two-stage stochastic optimization model that explicitly considers uncertain fuel and carbon emission prices, as well as potential retrofits along the lifetime. The bi-objective setup of the model shows how the choice of optimal power system changes with reduced emission levels. Methanol and LNG configurations appear to be relatively robust initial choices due to their ability to run on fuel derived from different feedstocks, and their better retrofittability towards ammonia or hydrogen. From a policy perspective, our model provides insight into the effect of the different types of carbon pricing mechanisms on a shipowner's decisions.
In this paper, we study a problem that integrates the vessel scheduling problem with the berth allocation into a collaborative problem denoted as the multi-port continuous berth allocation problem (MCBAP). This problem optimizes the berth allocation of a set of ships simultaneously in multiple ports while also considering the sailing speed of ships between ports. Due to the highly combinatorial character of the problem, exact methods struggle to scale to large-size instances, which points to exploring heuristic methods. We present a mixed-integer problem formulation for the MCBAP and introduce an adaptive large neighborhood search (ALNS) algorithm enhanced with a local search procedure to solve it. The computational results highlight the method's suitability for larger instances by providing high-quality solutions in short computational times. Practical insights indicate that the carriers’ and terminal operators’ operational costs are impacted in different ways by fuel prices, external ships at port, and the modeling of a continuous quay.
As a young researcher—admittedly a long time ago—I was struggling with capturing the connections of the many published articles on logistics management. Apparently, many articles dealt with the same topics, yet they were not the same. There seemed to be different viewpoints on what was a scientific contribution and what kinds of methods were allowed. Why did everyone not agree with these questions? Without an understanding of the different research traditions, it was difficult to compare results, validate them and create a meaningful discussion of the various contributions.
Within the Nordic research community, which consists of economists, engineers and management researchers, there were several answers to these questions. In this community, I learnt about systems from engineers. Then, it became clear that there are various philosophies of science that do not have the same understanding of what a theory is and what appropriate methods are. I was searching the philosophy of science literature for a systems perspective and the research implications of such a perspective. To my surprise, I did not find it here, but luckily, I came across a book about methodologies in business research where the systems approach was one of three approaches. I also learnt that, depending on the methodology, the term theory has a different meaning depending on the philosophy of science it originates from. That made a lot of sense to me. Understanding this better, I published my research on this topic in “Schools in Logistics Research” in 2004 (Gammelgaard, 2004). This rather old article is still my daily research guide.