About the Project

Update 10 August 2017: Due to the merger between Aalesund University College (www.hials.no) and NTNU (www.ntnu.edu), the hials domain will no longer be maintained. Therefore, the DRAMA website has been moved in its entirety to


The research project Dynamic Resource Allocation with Maritime Application (DRAMA) was funded by Regionalt Forskningsfond (RFF) Midt-Norge and the Research Council of Norway,  grant no. ES504913. A complete final report can be downloaded here.

For more information, please read the project description (also available in Norwegian).

The main goal of the project was to develop new and stringent algorithms for fleet optimisation based on methods from areas such as artificial intelligence, cybernetics, stochastic optimisation, and others.


Figure 1: Ship traffic along pink corridor along northern Norwegian coast. NOR VTS is the vessel traffic service centre in Vardø.

In particular, the project focussed on the the tug vessel preparedness in the north of Norway (see Figure 1). Annually more than 1500 high risk ships transit along the Norwegian coast, out of which about 300 carry oil or petroleum-related cargo. A fleet of three tugs as depicted in Figure 3 (two tugs since January 2014) need to be dynamically positioned along the coast in order to reduce the risk of oil tankers or other ships causing oil spill from drift grounding accidents.


Figure 2: The tug fleet of the Norwegian Coastal Administration.

Figure 3 shows how the problem can be modelled in 1D, where tugs have to be positioned along a line close to the coast, whereas oil tankers need to follow a corridor further out at sea. A suitable position for each tug is dependent on the collective positions of all the tugs, the current traffic situation, wind and weather, geography, ocean currents, and wave heights.


Figure 3: 1D model for dynamic optimisation of tug fleet positions.

The research question thus becomes:

How can the tugs be dynamically positioned in an optimal manner along the Norwegian coast such that the risk of drift grounding accidents is minimised?

An optimal solution to this question is shown in Figure 4 below:


Figure 4: Optimal mixed integer programming (MIP) solution to the tug fleet optimal positioning problem.


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