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.
@article{arxiv.1210.5035,
title = {A Comparative Study of State Transition Algorithm with Harmony Search and Artificial Bee Colony},
author = {Xiaojun Zhou},
journal= {arXiv preprint arXiv:1210.5035},
year = {2013}
}