A nature-inspired evolutionary algorithm based on spiral movements

In this paper, we present a nature-inspired evolutionary algorithm which is capable of solving real-valued optimization problems. The novel algorithm employs attraction and mutation. Attraction, based on the observation of spiral movements encountered in nature and the universe, is implemented using a dynamic system model. The proposed operator incorporating with the dynamic mutation works with the population-based technique to iteratively evolve into better and better solutions. To demonstrate its efficiency and accuracy, the proposed algorithm is evaluated on a variety of real-valued benchmark functions.