Solving IEEE CEC-2013 Real Parameter Optimization Problems using Harmony Search Algorithm

The Harmony Search Algorithm is an emerging meta-heuristic optimization algorithm. It mimics the behavior of a music orchestra for solving searching and optimization problems. The algorithm needs only a few control parameters like population size and the number of iterations. This paper presents an experimental implementation and analysis of the Harmony search algorithm on the IEEE Congress on Evolutionary Computation-2013 real parameter optimization problems test suite. This test suit contains 28 benchmark optimization functions including basic unimodal, multimodal and composition functions. The performance of the harmony search algorithm is analyzed and compared on all benchmark functions in lower dimensions (2 and 5), and in higher dimensions (10, 30, 50, and 100).