  In this paper we consider the scalability of Multi-Angle QAOA with respect to
the number of QAOA layers. We found that MA-QAOA is able to significantly
reduce the depth of QAOA circuits, by a factor of up to 4 for the considered
data sets. However, MA-QAOA is not optimal for minimization of the total QPU
time. Different optimization initialization strategies are considered and
compared for both QAOA and MA-QAOA. Among them, a new initialization strategy
is suggested for MA-QAOA that is able to consistently and significantly
outperform random initialization used in the previous studies.
