  We focus on a comparative study of three recently developed nature-inspired
optimization algorithms, including state transition algorithm, harmony search
and artificial bee colony. Their core mechanisms are introduced and their
similarities and differences are described. Then, a suit of 27 well-known
benchmark problems are used to investigate the performance of these algorithms
and finally we discuss their general applicability with respect to the
structure of optimization problems.
