Problem solving by intelligent water drops

By Hamed Shah-Hosseini. IEEE Congress on Evolutionary Computation, 2007

338 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/bf159ee64cf5f59c6470939ae6ba4f60ffb27b20

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In Artificial Intelligence

In Computational Theory and Mathematics

Citations in the corpus

Black hole: A new heuristic optimization approach for data clustering (2013, background): “In the IWD algorithm, several artificial water drops cooperate to change their environment in such a way that the optimal path is revealed as the one with the lowest soil on its links [80].”
Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems (2022, neutral): “Hosseini (2007) 25.”
RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method (2021, methodology): “7), the following conclusions can be obtained:  Concerning the convergence rate, the IWO, WCA, and CS algorithms displayed weak performances in optimizing the UFs and MFs, followed by the WOA and GWO algorithms.”
Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm (2019, methodology): “2001 4231 [104] Gravitational search optimization algorithm Webster and Bernhard 2003 29 [105] Big bang–big crunch-based optimization Erol and Eksin 2005 710 [106] Central force optimization Formato 2007 229 [107] Intelligent water drop Shah-Hosseini 2007 263 [108] River formation dynamics Rabanal e”
A Survey of Bio inspired Optimization Algorithms (2012, methodology): “IWD is an innovative population based method proposed by Hamed Shah-hosseini in 2007[12] .”
A Brief Review of Nature-Inspired Algorithms for Optimization (2013, background): “ search Rashedi et al. [50] Anarchic society optimization Shayeghi and Dadashpour [54] Harmony search Geem et al. [23] Artiﬁcial cooperative search Civicioglu [9] Intelligent water drop Shah-Hosseini [52] Backtracking optimization search Civicioglu [11] River formation dynamics Rabanal et al. [49] D”
Water wave optimization: A new nature-inspired metaheuristic (2015, background): “, have been extensively studied; on the other hand, a variety of novel EAs, such as invasive weed optimization (IWO) [9], water drops algorithm [10], biogeography-based optimization (BBO) [11], cuckoo search [12], fireworks algorithm [13], bat algorithm (BA) [14], etc.”
A review of population-based meta-heuristic algorithm (2013, background): “…Particle Swarm Optimization (PSO) [9, 10], Stochastic Diffusion Search (SDS) [11], Artificial Bee Colony (ABC) [12], Intelligent Water Drops (IWD) [13], River Formation Dynamics (RFD) [14], Gravitational Search Algorithm (GSA) [5] and Charged System Search (CSS) [16] are in the class of such…”
The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm (2009, methodology): “The IWD algorithm has been used for the travelling salesman’s problem (TSP) (Shah-Hosseini, 2007) and multiple (or multidimensional) knapsack problem (MKP) (Shah-Hosseini, 2008) with promising results.”