Comparison of Firefly, Cultural and the Artificial Bee Colony Algorithms for Optimization

Global optimization refers to the technique for finding the best element in the given domain by satisfying certain constraints. Optimization algorithms are classified as deterministic and heuristic. Deterministic algorithms provide guaranteed solutions but with high computational demand. Heuristic and metaheuristic algorithms have been successfully used in optimization problems. They provide a solution close to the optimum with a better speed and less complexity. In this paper three metaheuristic algorithms namely firefly, cultural and the artificial bee colony, algorithm have been investigated over benchmark function optimization. The results and numeric simulation include comparison of the algorithms in terms of minimization of the objective function. Results of Matlab implementation show that the firefly algorithm performs the optimization in the most accurate manner. Cultural algorithm is inferior to firefly and the ABC algorithm shows the poorest performance among the three.