  We present an analog version of the quantum approximate optimization
algorithm suitable for current quantum annealers. The central idea of this
algorithm is to optimize the schedule function, which defines the adiabatic
evolution. It is achieved by choosing a suitable parametrization of the
schedule function based on interpolation methods for a fixed time, with the
potential to generate any function. This algorithm provides an approximate
result of optimization problems that may be developed during the coherence time
of current quantum annealers on their way toward quantum advantage.
