  We empirically evaluate the finite-time performance of several
simulation-optimization algorithms on a testbed of problems with the goal of
motivating further development of algorithms with strong finite-time
performance. We investigate if the observed performance of the algorithms can
be explained by properties of the problems, e.g., the number of decision
variables, the topology of the objective function, or the magnitude of the
simulation error.
