Optimizing the Recovery Efficiency of Finnish Oil Combating Vessels in the Gulf of Finland Using Bayesian Networks

Oil transport has greatly increased in the Gulf of Finland
over the years, and risks of an oil accident occurring have risen. Thus, an
effective oil combating strategy is needed. We developed a Bayesian
Network (BN) to examine the recovery efficiency and optimal
disposition of the Finnish oil combating vessels in the Gulf of Finland
(GoF), Eastern Baltic Sea. Four alternative home harbors, five accident
points, and ten oil combating vessels were included in the model to find
the optimal disposition policy that would maximize the recovery
efficiency. With this composition, the placement of the oil combating
vessels seems not to have a significant effect on the recovery efficiency.
The process seems to be strongly controlled by certain random factors
independent of human action, e.g. wave height and stranding time of the
oil. Therefore, the success of oil combating is rather uncertain, so it is
also important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this type
of multidecision optimization. The methodology, results, and practices are further discussed.