  Test functions are important to validate and compare the performance of
optimization algorithms. There have been many test or benchmark functions
reported in the literature; however, there is no standard list or set of
benchmark functions. Ideally, test functions should have diverse properties so
that can be truly useful to test new algorithms in an unbiased way. For this
purpose, we have reviewed and compiled a rich set of 175 benchmark functions
for unconstrained optimization problems with diverse properties in terms of
modality, separability, and valley landscape. This is by far the most complete
set of functions so far in the literature, and tt can be expected this complete
set of functions can be used for validation of new optimization in the future.
