Nature-Inspired Metaheuristic Algorithms

By Xin-She Yang. 2008

4,201 citations recorded by the source corpus.

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Citations in the corpus

An Optimization Algorithm for Solving Systems of Singular Boundary Value Problems (2014, background): “To a degree, all stochastic methods attempt to make trade-off between exploitation and exploration [17].”
Multiobjective cuckoo search for design optimization (2013, background): “On the other hand, metaheuristic algorithms are very powerful in dealing with this kind of optimization, and there are many review articles and excellent textbooks [6,9,11,36,38,39,42].”
MPPT methods for solar PV systems: a critical review based on tracking nature (2019, methodology): “1 FA-based method: At first, the FA was presented in [94, 95].”
A Novel Order Reduction Method Using Cuckoo Search Algorithm (2015, methodology): “CS is a meta-heuristic algorithm which is recently developed by Yang and Deb [32].”
Firefly algorithm with chaos (2013, methodology): “To copewith this issue, global algorithms arewidely used [1].”
A comprehensive review of firefly algorithms (2013, methodology): “Besides attracting mating partners, the flashing light may also serve to warn off potential predators.”
A survey on nature inspired metaheuristic algorithms for partitional clustering (2014, background): “Literature review [44,45] reveals the recent trend to name all stochastic algorithms with randomization and local search as ‘metaheuristic’.”
Elephant Herding Optimization (2015, background): “…by this phenomenon, ACO [10, 11] was proposed by Dorigo et al. Recently, more effective swarm intelligence algorithms have been proposed, such as artificial bee colony (ABC) [12, 13], cuckoo search (CS) [14-20], bat algorithm (BA) [21-24], firefly algorithm (FA) [25-28], animal migration…”
Metaheuristic research: a comprehensive survey (2018, methodology): “…Programming (Yao et al. 1999) ES Evolution Strategies (Beyer and Schwefel 2002) ESA Elephant Search Algorithm (Deb et al. 2015) FA Firefly Algorithm (Yang 2008) FASO Foraging Agent Swarm Optimization (Barresi 2014) FEO Fish Electrolocation Optimization (Haldar and Chakraborty 2017) FFO Fruit Fly…”
Flower Pollination Algorithm for Global Optimization (2012, methodology): “…evolution of biological systems [9] and particle swarm optimization was based on the swarm behaviour of birds and ﬁsh [11, 12], which bat algorithm was based on the echolocation behaviour of microbats [21] and ﬁreﬂy algorithm was based on the ﬂashing light patterns of tropic ﬁreﬂies [18, 19].”
Firefly algorithm, stochastic test functions and design optimisation (2010, methodology): “The Fireﬂy Algorithm was developed by the author (Yang 2008, Yang 2009), and it was based on the idealized behaviour of the ﬂashing characteristics of ﬁreﬂies.”
A New Metaheuristic Bat-Inspired Algorithm (2010, methodology): “The former was inspired by the improvising process of composing a piece of music [4], while the latter was formulated based on the ﬂashing behaviour of ﬁreﬂies [14].”