Improving the performance of harmony search using opposition-based learning and quadratic interpolation
Mahamed G. H. Omran, Zong Woo Geem, Ayed A. Salman · International Journal of Mathematical Modelling and Numerical Optimisation · 2010
Harmony search (HS) is a recently spotlighted metaheuristic optimisation method imitating the music improvisation process where musicians improvise their instruments' pitches searching for a perfect state of harmony. In this paper, the effect of using opposition-based learning and quadratic interpolation is investigated. Three variants are proposed and the performance of these methods is investigated and compared with HS and other recent methods when applied to several benchmark functions. The experiments conducted show that the proposed methods generally outperformed the other methods when applied to the benchmark problems. Moreover, the performance of the proposed methods when applied to high-dimensional problems is investigated.