  We study the effect of the anneal path control per qubit, a new user control
feature offered on the D-Wave 2000Q quantum annealer, on the performance of
quantum annealing for solving optimization problems by numerically solving the
time-dependent Schr\"odinger equation for the time-dependent Hamiltonian
modeling the annealing problems. The anneal path control is thereby modeled as
a modified linear annealing scheme, resulting in an advanced and retarded
scheme. The considered optimization problems are 2-SAT problems with 12 Boolean
variables, a known unique ground state and a highly degenerate first excited
state. We show that adjustment of the anneal path control can result in a
widening of the minimal spectral gap by one or two orders of magnitude and an
enhancement of the success probability of finding the solution of the
optimization problem. We scrutinize various iterative methods based on the spin
floppiness, the average spin value, and on the average energy and describe
their performance in boosting the quantum annealing process.
