A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms

By Pinar Çivicioglu, Erkan Besdok. Artificial Intelligence Review, 2011

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Cuckoo search: recent advances and applications (2013, background): “…analysis point of view, a conceptural comparison of cuckoo search with particle swarm optimization (PSO), diﬀerential evolution (DE), artiﬁcial bee colony (ABC) by Civicioglu and Desdo [8] suggested that cuckoo search and diﬀerential evoluton algorithms provide more robust results than PSO and ABC.”
Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm (2012, methodology): “…certain problem, Computational-Intelligence based optimization algorithms are quite successful in solving numerical optimization problems (e.g., Ant-Colony Optimization Algorithm (Ant Colony) (Dorigo et al., 1996), ABC, PSO, Cuckoo-Search Algorithm (Yang and Deb, 2010; Civicioglu and Besdok, 2011).”
One Pixel Attack for Fooling Deep Neural Networks (2017, background): “Moreover, it has mechanisms in the population selection phase that keep the diversity such that in practice it is expected to efficiently find higher quality solutions than gradient-based solutions or even other kinds of EAs [4].”