Optimization algorithms are popular approaches to solving problems in many field. By considering the performance criteria of the optimization algorithms, optimization algorithms suitable for the topic are selected. In this study, the performance criteria of the five optimization algorithms, which have the same mathematical test functions and the parameter values of these functions and the decision variables, the number of populations and the number of execution cycles of the algorithm, are compared. Artificial Bee Colony Algorithm, Particle Swarm Optimization Algorithm, Fire Beetle Algorithm, Symbiotic Organism Algorithm and Biogeography Based Optimization Algorithm are used as optimization algorithms. Performance measures of these five optimization algorithms are calculated on three different benchmarking algorithms. The calculation results are presented as numerical values.