Over the recent decades, there has been an increasing focus on energy-efficient operation of vessels. It has become part of the political agenda, where regulation is the main driver, but the maritime industry itself has also been driven towards more energy-efficient operation of the vessels, due to increasing fuel costs. Improving the energy efficiency on board vessels is not only a technical issue - factors such as awareness of the problem, knowledge skills and motivation are also important parameters that must be considered.
The paper shows how training in energy-efficient operation and awareness can affect the energy consumption of vessels. The study is based on navigational, full-mission simulator tests conducted at the International Maritime Academy SIMAC. A full-mission simulator is an image of the world allowing the students to obtain skills through learning-by-doing in a safe environment. Human factors and technical issues were included and the test sessions consisted of a combination of practical simulator exercises and reflection workshops.
The result of the simulator tests showed that a combination of installing technical equipment and raising awareness - making room for reflections-on and in-action - has a positive effect on energy consumption. The participants, on average, saved approximately 10% in fuel.
The increasing focus on energy efficient operation of vessels can be seen in both legislation and research. This paper focuses attention on the human factor influencing energy efficiency and explores the conditions for improving energy efficiency in working vessels taking situational awareness (SA) theory into consideration.
The study builds on two cases: an offshore supply vessel for the oil & gas industry and an installation vessel for wind turbines. The study used qualitative methods based on 49 interviews with seafarers and onshore employees from the vessels and shipping companies.
The study has identified that the energy efficiency of a ship is mainly influenced by legislation and the praxis formed on board. The results showed that the theory on SA is very a useful tool in explaining the factors affecting the energy efficiency of a vessel and the praxis.
The study has shown that obtaining a more energy efficient operation is complex and depends not only on the officer on board the ship. The improvement of energy efficiency is possible, but there is a need to understand the complexity of the issue and to involve both the crew and the entire system around the ship, and to obtain a shared perspective of energy efficient operation. Furthermore, in order to improve energy efficiency in shipping companies, there is a need to support the seafarers in gaining more skills for operating the ship more energy efficiently; to do this the right way there is a need to create an understanding of the system by the authorities, ship owners and charterers.
The literature on liner shipping includes many models on containership speed optimization, fleet deployment, fleet size and mix, network design and other problem variants and combinations. Many of these models, and in fact most models at the tactical planning level, assume a fixed revenue for the ship operator and as a result they typically minimize costs. This treatment does not capture a fundamental characteristic of shipping market behavior, that ships tend to speed up in periods of high freight rates and slow down in depressed market conditions. This paper develops a simple model for a fixed route scenario which, among other things, incorporates the influence of freight rates, along with that of fuel prices and cargo inventory costs into the overall decision process. The objective to be maximized is the line’s average daily profit. Departing from convention, the model is also able to consider flexible service frequencies, to be selected from a broader set than the standard assumption of one call per week. It is shown that this may lead to better solutions and that the cost of forcing a fixed frequency can be significant. Such cost is attributed either to additional fuel cost if the fleet is forced to sail faster to accommodate a frequency that is higher than the optimal one, or to lost income if the opposite is the case. The impact of the line’s decisions on CO2 emissions is also examined and illustrative runs of the model are made on three existing services.
Having a well-designed liner shipping network is paramount to ensure competitive freight rates, adequate capacity on trade-lanes, and reasonable transportation times. The most successful algorithms for liner shipping network design make use of a two-phase approach, where they first design the routes of the vessels, and then flow the containers through the network in order to calculate how many of the customers’ demands can be satisfied, and what the imposed operational costs are. In this article, we reverse the approach by first flowing the containers through a relaxed network, and then design routes to match this flow. This gives a better initial solution than starting from scratch, and the relaxed network reflects the ideas behind a physical internet of having a distributed multi-segment intermodal transport. Next, the initial solution is improved by use of a variable neighborhood search method, where six different operators are used to modify the network. Since each iteration of the local search method involves solving a very complex multi-commodity flow problem to route the containers through the network, the flow problem is solved heuristically by use of a fast Lagrange heuristic. Although the Lagrange heuristic for flowing containers is 2–5% from the optimal solution, the solution quality is sufficiently good to guide the variable neighborhood search method in designing the network. Computational results are reported, showing that the developed heuristic is able to find improved solutions for large-scale instances from LINER-LIB, and it is the first heuristic to report results for the biggest WorldLarge instance.
In transportation of goods in large container ships, shipping industries need to minimize the time spent at ports to load/unload containers. An optimal stowage of containers on board minimizes unnecessary unloading/reloading movements, while satisfying many operational constraints. We address the basic container stowage planning problem (CSPP). Different heuristics and formulations have been proposed for the CSPP, but finding an optimal stowage plan remains an open problem even for small-sized instances. We introduce a novel formulation that decomposes CSPPs into two sets of decision variables: the first defining how single container stacks evolve over time and the second modeling port-dependent constraints. Its linear relaxation is solved through stabilized column generation and with different heuristic and exact pricing algorithms. The lower bound achieved is then used to find an optimal stowage plan by solving a mixed-integer programming model. The proposed solution method outperforms the methods from the literature and can solve to optimality instances with up to 10 ports and 5,000 containers in a few minutes of computing time.
This paper contributes to the understanding of competition and industry evolution by analyzing how submarket dynamics and agency influence the development of the emerging industrial field of Danish offshore wind energy. We argue that industry evolution is sensitive to the balance between integration, overlap and disintegration across submarkets. This balance depends on how strategic intent and behavior influence submarket dynamics, leading to the conclusion that effects of agency and managerial intent should play a more prominent role in studies of industry evolution.
The use of the seas and oceans is generally regulated by the United Nations through the UN Convention on the Law of the Sea, which defines the rights and responsibilities. However, with the rapidly increasing use of the sea and oceans it is inevitable that conflicts may arise. Accordingly, there has been an increasing international recognition of the need to manage human activities that influence the marine environment and its ecosystems in an integrated, cross-sectoral manner. Recently, Maritime Spatial Planning (MSP) has gained significant attention as a new paradigm aiming at minimizing the conflicts among different sea uses through involving various stakeholders and sectors while aiming for sustainable growth. The aim of this research is to build a conceptual model for a Data Infrastructure to support marine space in a transnational context addressing the challenges related to the increasing use of marine areas and resources. The work was carried out in a close cooperation between several public authorities and research institutes in the Baltic Sea Region.
A fuel levy is one of the market-based measures (MBMs) currently under consideration at the International Maritime Organization. MBMs have been proposed to improve the energy efficiency of the shipping sector and reduce its emissions. This paper analyses the economic and environmental implications of two types of levy on shipping bunker fuels by means of an analytical model built on the cobweb theorem. A unit-tax per ton of fuel and an ad-valorem tax, enforced as a percentage of fuel prices, are examined. In both cases, a speed and fuel-consumption reduction equivalent to an improvement in the energy efficiency of the sector would be expected as a result of the regulation enforcement. The speed reduction in the unit-tax case depends on fuel prices and the tax amount, whereas in the ad-valorem case it relies upon the enforced tax percentage.
Both schemes lead to industry profit decline, the extent of which depend on the structure of the levy and market conditions. Since there is concern that the costs resulting from the policy will be passed from shipping companies to their customers along the supply chain, the paper dwells on how the costs arising from the enforcement of the levy will be actually allocated between ship-owners and operators, and cargo-owners. In a market characterised by high freight rates and with no or limited excess capacity, a higher percentage of the total tax amount is transferred from ship-owners to shippers. In case of a recession the opposite happens.
The selection of alternative energy sources for shipping can effectively mitigate the problems of high energy consumption and severe environmental problems caused by shipping. However, it is usually difficult for decision makers to select the most sustainable alternative energy source for shipping among multiple alternatives due to the complexity of considering different aspects of performances and the lack of information. This study developed a novel multi-criteria decision-making method that combines Dempster-Shafer theory and a trapezoidal fuzzy analytic hierarchy process for alternative energy source selection under incomplete information conditions. According to the developed method, nuclear power has been recognized as the most sustainable alternative energy source for shipping, followed by liquefied natural gas (LNG) and wind power, and sensitivity analysis reveals that the weights of the criteria have significant on the sustainability sequence of the three alternative energy sources for shipping. The developed method can be popularized for selecting the most sustainable alternative energy source despite incomplete information.
Seaborne trade is the lynchpin in almost every international supply chain, and about 90% of non-bulk cargo worldwide is transported by container. In this survey we give an overview of data-driven optimization problems in liner shipping. Research in liner shipping is motivated by a need for handling still more complex decision problems, based on big data sets and going across several organizational entities. Moreover, liner shipping optimization problems are pushing the limits of optimization methods, creating a new breeding ground for advanced modelling and solution methods. Starting from liner shipping network design, we consider the problem of container routing and speed optimization. Next, we consider empty container repositioning and stowage planning as well as disruption management. In addition, the problem of bunker purchasing is considered in depth. In each section we give a clear problem description, bring an overview of the existing literature, and go in depth with a specific model that somehow is essential for the problem. We conclude the survey by giving an introduction to the public benchmark instances LINER-LIB. Finally, we discuss future challenges and give directions for further research.