| dc.description.abstract | Increasing food prices in Europe demands a heightened attention to resource utilisation.
This leads to a great potential to better utilize one of the most abundant biomasses on
earth: krill. These tiny crustaceans consist of more than 25% lipids containing omega-3
fatty acids and more than 60% high quality proteins (Tou et al., 2007). Today krill products
are produced both for pets and humans, and it is especially popular in aquaculture feed.
There is, however, still a great potential for this resource to be utilized better and in an
even more effective way.
This thesis aims to optimize the supply chain, and more specifically the fishing operation in
the Antarctic krill fishing business. A case study of the Aker BioMarine fishing operation
is conducted for a single season where a schedule is created for their support vessel, a
vessel used to transport krill, crew, fuel, and equipment between the fishing vessels in the
Antarctic Ocean and the shore of South America, to maximize the total krill harvested
while keeping costs down. This was done using a mixed integer linear programming model
with a rolling horizon approach. In addition to using the numbers from the 2021 season,
the model was also tested on two scenarios: one where the fishing rates were increased by
50%, and one where the travelling times between all locations were increased. This was to
see the model’s performance under more lucrative seasons, and seasons with bad weather.
The base case findings show that the MILP approach effectively schedules the season so
that the support vessel has as few trips as possible, while allowing the fishing vessels
to have no ineffective days. This was also the case in the scenario with the increased
travelling times. The results for the scenario with increased fishing rates were slightly
worse. The support vessel still had no problem managing to deliver all krill while keeping
the fishing vessels active every day. It used unnecessarily many trips to do so. We allocate
this inefficiency to problems related to the rolling horizon approach.
This study shows the effectiveness in using mathematical modelling to schedule support
vessels in fishing operations to keep the operation effective while cutting unnecessary
costs. | en_US |
