  When performing a Monte Carlo calculation, the running time should in
principle be much longer than the autocorrelation time in order to get reliable
results. Among different lattice fermion models, the Holstein model is
notorious for its particularly long autocorrelation time. In this work, we
employ the Wang-Landau algorithm in the determinant quantum Monte Carlo to
achieve the flat-histogram sampling in the "configuration weight space", which
can greatly reduce the autocorrelation time by sacrificing some sampling
efficiency. The proposal is checked in the Holstein model on both square and
honeycomb lattices. Based on such a Wang-Landau assisted determinant quantum
Monte Carlo method, some models with long autocorrelation times can now be
simulated possibly.
