  We present a detailed comparison of two approaches, the use of a
pre-calculated database and simulated annealing (SA), for fitting the continuum
spectral energy distribution (SED) of astrophysical objects whose appearance is
dominated by surrounding dust. While pre-calculated databases are commonly used
to model SED data, only few studies to date employed SA due to its unclear
accuracy and convergence time for this specific problem. From a methodological
point of view, different approaches lead to different fitting quality, demand
on computational resources and calculation time. We compare the fitting quality
and computational costs of these two approaches for the task of SED fitting to
provide a guide to the practitioner to find a compromise between desired
accuracy and available resources. To reduce uncertainties inherent to real
datasets, we introduce a reference model resembling a typical circumstellar
system with 10 free parameters. We derive the SED of the reference model with
our code MC3D at 78 logarithmically distributed wavelengths in the range
[0.3um, 1.3mm] and use this setup to simulate SEDs for the database and SA. Our
result shows directly the applicability of SA in the field of SED modeling,
since the algorithm regularly finds better solutions to the optimization
problem than a pre-calculated database. As both methods have advantages and
shortcomings, a hybrid approach is preferable. While the database provides an
approximate fit and overall probability distributions for all parameters
deduced using Bayesian analysis, SA can be used to improve upon the results
returned by the model grid.
