COMPARISON OF THE PERFORMANCES OF DIFFERENTIAL EVOLUTION, PARTICLE SWARM OPTIMIZATION AND HARMONY SEARCH ALGORITHMS ON BENCHMARK FUNCTIONS

In the literature, there are many efficient metaheuristic algorithms for optimizing real-valued objective functions. In this work, Particle Swarm Optimization (PSO) algorithm, Differential Evolution (DE) algorithm and Harmony Search (HS) algorithm are compared on the basis of speed of convergence of the algorithms. In order to achieve this goal, a set of benchmark functions that have different characteristics are used.