ABFIA: A hybrid algorithm based on artificial bee colony and Fibonacci indicator algorithm

The artificial bee colony (ABC) is a metaheuristic optimization algorithm known for its simplicity, flexibility, and efficiency. The algorithm, however, suffers from slow convergence due to a lack of a powerful local search capability. The Fibonacci indicator algorithm (FIA), on the other hand, is a recently proposed derivative-free metaheuristic that incorporates a powerful local search mechanism based on the line search method. This paper proposes hybridizing the artificial bee colony with the Fibonacci indicator algorithm to achieve strong exploration and highly efficient exploitation capabilities. We show that the hybrid algorithm is better than ABC and FIA and delivers superior outcomes for various optimization functions widely used in the literature, including 20 scalable basic and ten complex CEC2019 test functions.