Firefly algorithm with chaos

By Amir H. Gandomi, Xin-She Yang, Siamak Talatahari, Amir Hossein Alavi. Communications in nonlinear science & numerical simulation, 2013

812 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/c7b0653e5e04ece8cfc9b9459d8e9e8f218c7e5a

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In Statistical and Nonlinear Physics

Citations in the corpus

A comprehensive review of firefly algorithms (2013, methodology): “Elitist firefly algorithm [46] Binary represented firefly algorithm [47] [48] [49] [65] Gaussian randomized firefly algorithm [54] [55] Lévy flights randomized firefly algorithm [55] [58] [59] Chaos randomized firefly algorithm [60] [62] Parallel firefly algorithm [63] [64]”
A survey on new generation metaheuristic algorithms (2019, background): “# Acronym Metaheuristic Inventors, Year 1 HS Harmony Search Geem et al. (2001) 2 BFO Bacterial Foraging Opt. Passino (2002) 3 ABC Artificial Bee Colony Karaboga (2005) 4 BBO Biogeography-based Opt. Simon (2008) 5 CS Cuckoo Search Yang and Deb (2009) 6 GSA Gravitational Search Algorithm Rashedi et al”
Chaotic Local Search-Based Differential Evolution Algorithms for Optimization (2021, methodology): “Chaotic properties have been used in other newly proposed swarm intelligence optimization algorithms, such as chaotic BBO [40], chaotic bat algorithm [29], [41], chaotic cuckoo search [42], chaotic fruit fly optimization algorithm [43], chaotic krill herd algorithm [44], firefly algorithm with chaos”
Bio inspired computing - A review of algorithms and scope of applications (2016, methodology): “Cuckoo search (Yang & Deb, 2009; Gandomi et al., 2013; Yang & Deb, 2013) was developed for addressing single or multi-objective problems under complex nonlinear constraints.”
Chaos-enhanced accelerated particle swarm optimization (2013, methodology): “Previously, chaotic sequences have been used together with some heuristic optimization algorithms to produce hybrid algorithms, and such hybridization has been successful in combination with GA [6], harmony search (HS) [7], simulated annealing (SA) [8], imperialist competitive algorithm [9] and fire”
Biogeography-based optimisation with chaos (2014, neutral): “In this paper we use similar initial values to those of [5, 32].”
Feature selection via a novel chaotic crow search algorithm (2017, background): “Some of them are chaotic ant swarm optimization (CASO) [5], chaotic genetic algorithm (CGA) [1, 49], chaotic particle swarm (CPSO) [20, 21, 50], chaotic pattern search (CPS) [54], chaotic simulated annealing algorithm (CSA) [33], chaotic differential evolution algorithm (CDEA) [22], chaotic biogeogr”
Chaotic Krill Herd algorithm (2014, methodology): “Up to now, the chaos theory has been successfully combined with several meta-heuristic optimization methods [13].”
A comprehensive survey on recent metaheuristics for feature selection (2022, background): “has proven to be more reliable in terms of finding the global optimum [158].”
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur's entropy (2014, background): “Diversification intends to explore the search space more efficiently, frequently by randomization (Gandomi et al., 2012; Gandomi et al., 2013a).”
Firefly algorithm with neighborhood attraction (2017, methodology): “In [17], 12 different chaotic maps were used to update γ and β.”