  We propose a method for Monte Carlo simulation of statistical physical models
with discretized energy. The method is based on several ideas including the
cluster algorithm, the multicanonical Monte Carlo method and its acceleration
proposed recently by Wang and Landau. As in the multibondic ensemble method
proposed by Janke and Kappler, the present algorithm performs a random walk in
the space of the bond population to yield the state density as a function of
the bond number. A test on the Ising model shows that the number of Monte Carlo
sweeps required of the present method for obtaining the density of state with a
given accuracy is proportional to the system size, whereas it is proportional
to the system size squared for other conventional methods. In addition, the new
method shows a better performance than the original Wang-Landau method in
measurement of physical quantities.
