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6 CONCLUSIONS AND FUTURE
WORK
We have presented a formulation of the Tail Assign-
ment Problem as a QUBO model to be solved using
QA based on the current commercial solution devel-
oped by D-Wave Systems. Our results demonstrate
that using an hybrid solver for the proposed QUBO
model may represent a considerable advantage in the
probability of finding valid non-expensive solutions
when compared with a classical solver. Nonetheless,
it is relevant to note that, even though it may show
encouraging results, quantum computation is in an
early stage and, therefore, the current limitations do
not allow scaling it to complete real-world datasets.
Throughout this study, we opted to implement mul-
tiple simplifications to narrow the scope of the prob-
lem in analysis. A non-consideration of minor main-
tenance tasks is not realistic as they have to occur in
a real scenario. Furthermore, a robust approach may
be a pivotal achievement as flight delays are frequent
and tight schedules can be significantly affected by
that. Additionally, to understand the effectiveness in
a deeper level of the proposed modelling technique,
when applied to multiple solvers using different sce-
narios, it would be important to run more tests using
different datasets. Finally, as HSS revealed to perform
better for solving this problem than using only a clas-
sical algorithm such as SA, further studies on hybrid
solvers could be relevant for a better understanding
on the real advantage of using such technique to solve
complex optimisation problems.
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