The intelligent water drops algorithm: why it cannot be considered a novel algorithm

In this article, we rigorously analyze the intelligent water drops (IWD) algorithm, a metaphor-based approach for the approximate solution of discrete optimization problems proposed by Shah-Hosseini (in: Proceedings of the 2007 congress on evolutionary computation (CEC 2007), IEEE Press, Piscataway, NJ, pp 3226–3231, 2007 ). We demonstrate that all main algorithmic components of IWD are simplifications or special cases of ant colony optimization (ACO), and therefore, IWD is simply a particular instantiation of ACO. We show that the natural metaphor of “water drops flowing in rivers removing the soil from the riverbed” , the source of inspiration of IWD, is unnecessary, misleading and based on unconvincing assumptions of river dynamics and soil erosion that lack a real scientific rationale. We carry out a detailed review of modifications and extensions proposed to IWD since its first publication in 2007. We find that research on IWD is for the most part misguided and that the vast majority of the ideas explored in the literature on IWD have been studied many years before in the context of ACO. Finally, we discuss the use of natural metaphors as a source of inspiration for optimization algorithms, which has become an extremely popular trend in the last 15 years, and propose some criteria to limit their usage to the cases in which the metaphor is indeed useful.