In recent past, many new nature-inspired optimization techniques have been emerged in the field of science and engineering that have proven to be efficient to solve optimization problems. One such method that makes use of metaheuristics for optimization, inspired by the nature of chemical reactions is Chemical Reaction Optimization (CRO). It is a powerful metaheuristic which mimics the interactions of molecules in chemical reactions to search for the global optimum. In this paper, we used this technique to solve well-known separable and non-separable benchmark functions. The simulation results showed that all problems showed good performance. A measurement metric is used reporting the best, average, worst, success rate and execution time. Different experiments were conducted by scaling the iterations, population size and energy level.