Scheduling Support Vessels In Antarctic Krill Fishing : A Mixed-Integer Linear Programming Model With A Rolling Horizon Approach

2023

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.