Global optimization, real-world optimization problems, nature-inspired algorithms, adaptive differ-ential evolution, experimental comparison

Eight popular nature inspired algorithms are compared with the blind random search and three ad-vanced adaptive variants of differential evolution (DE) on real-world problems benchmark collected for CEC 2011 algorithms competition. The results show the good performance of the adaptive DE variants and their superiority over the other algorithms in the test problems. Some of the nature-inspired algorithms perform even worse that the blind random search in some problems. This is a strong argument for recommendation for application, wherewell-verified algorithm successful in competitions should be preferred instead of developing some new algorithms.