  We introduce multiple parametrized circuit ans\"atze and present the results
of a numerical study comparing their performance with a standard Quantum
Alternating Operator Ansatz approach. The ans\"atze are inspired by mixing and
phase separation in the QAOA, and also motivated by compilation considerations
with the aim of running on near-term superconducting quantum processors. The
methods are tested on random instances of a weighted quadratic binary
constrained optimization problem that is fully connected for which the space of
feasible solutions has constant Hamming weight. For the parameter setting
strategies and evaluation metric used, the average performance achieved by the
QAOA is effectively matched by the one obtained by a "mixer-phaser" ansatz that
can be compiled in less than half-depth of standard QAOA on most
superconducting qubit processors.
