An Artificial Bee Colony algorithm for solving dynamic optimization problems

Artificial Bee Colony (ABC) is a fast and robust algorithm to solve various optimization problems with complex nonlinearity. Especially, ABC is effective for high dimensional problems, compared with the other metaheuristic algorithms. However, the basic ABC is assumed to be used to static optimization problems and has not been sufficiently considered for dynamic optimization problems including temporal changes of environments. Recently, improved ABC methods for solving dynamic optimization problems have been proposed. However, it is difficult for these methods to balance the flexibility to temporal changes of environments and the convergent speed to solutions. This paper proposes an ABC algorithm for solving dynamic optimization problems with simple procedures. The proposed method can realize fast solution search for various dynamic optimization problems, suppressing excessive convergence to limited solutions. In the numerical simulations, the effectiveness of the proposed method is verified.