Firefly algorithm - Revision history

Bkell: /* Algorithm */ MOS:INDENT; delete stray letters; decap "particle swarm optimization"

2025-02-09T01:16:13Z

Algorithm: MOS:INDENT; delete stray letters; decap "particle swarm optimization"

← Previous revision		Revision as of 01:16, 9 February 2025
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	The main update formula for any pair of two fireflies <math>\mathbf{x}_i </math> and <math>\mathbf{x}_j </math> is		The main update formula for any pair of two fireflies <math>\mathbf{x}_i </math> and <math>\mathbf{x}_j </math> is
	:: <math>\mathbf{x}_i^{t+1}=\mathbf{x}_i^t + \beta \exp[-\gamma r_{ij}^2] (\mathbf{x}_j^t - \mathbf{x}_i^t) +\alpha_t \boldsymbol{\epsilon}_t </math>		<math display="block">\mathbf{x}_i^{t+1}=\mathbf{x}_i^t + \beta \exp[-\gamma r_{ij}^2] (\mathbf{x}_j^t - \mathbf{x}_i^t) +\alpha_t \boldsymbol{\epsilon}_t </math>
	where <math>\alpha_t </math> is a parameter controlling the step size, while <math>\boldsymbol{\epsilon}_t </math> is a vector drawn from a Gaussian or other		where <math>\alpha_t </math> is a parameter controlling the step size, while <math>\boldsymbol{\epsilon}_t </math> is a vector drawn from a Gaussian or other
	distribution.~~zae~~		distribution.

	It can be shown that the limiting case <math>\gamma \rightarrow 0 </math> corresponds to the standard [[~~Particle~~ ~~Swarm~~ ~~Optimization~~]] (PSO). In fact, if the inner loop (for j) is removed and the brightness <math>I_j</math> is replaced by the current global best <math>g^*</math>, then FA essentially becomes the standard PSO.		It can be shown that the limiting case <math>\gamma \rightarrow 0 </math> corresponds to the standard [[particle swarm optimization]] (PSO). In fact, if the inner loop (for j) is removed and the brightness <math>I_j</math> is replaced by the current global best <math>g^*</math>, then FA essentially becomes the standard PSO.

	== Criticism ==		== Criticism ==

OAbot: Open access bot: hdl updated in citation with #oabot.

2024-01-05T20:09:17Z

Open access bot: hdl updated in citation with #oabot.

← Previous revision		Revision as of 20:09, 5 January 2024
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	== Criticism ==		== Criticism ==

	Nature-inspired [[metaheuristic]]s in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite book\|first=Michael A.\|last=Lones\|title=Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation \|chapter=Metaheuristics in nature-inspired algorithms \|year=2014\|pages=1419–1422\|chapter-url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825\|s2cid=14997975 }}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>		Nature-inspired [[metaheuristic]]s in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite book\|first=Michael A.\|last=Lones\|title=Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation \|chapter=Metaheuristics in nature-inspired algorithms \|year=2014\|pages=1419–1422\|chapter-url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825\|s2cid=14997975 }}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free\|hdl=10419/178253\|hdl-access=free}}</ref>

	==See also==		==See also==

Headbomb: clean up

2023-08-08T06:44:10Z

clean up

← Previous revision		Revision as of 06:44, 8 August 2023
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	== Criticism ==		== Criticism ==

	Nature-inspired [[~~Metaheuristic\|metaheuristics~~]] in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite book\|first=Michael A.\|last=Lones\|title=Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation \|chapter=Metaheuristics in nature-inspired algorithms ~~\|date=2014~~ \|year=2014\|pages=1419–1422\|chapter-url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825\|s2cid=14997975 }}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>		Nature-inspired [[metaheuristic]]s in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite book\|first=Michael A.\|last=Lones\|title=Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation \|chapter=Metaheuristics in nature-inspired algorithms \|year=2014\|pages=1419–1422\|chapter-url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825\|s2cid=14997975 }}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>

	==See also==		==See also==
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	==External links==		==External links==
	* [https://www.mathworks.com/matlabcentral/fileexchange/29693-firefly-algorithm] Files of the Matlab programs included in the book: Xin-She Yang, Nature-Inspired Metaheuristic Algorithms, Second Edition, Luniver Press, (2010).		* [https://www.mathworks.com/matlabcentral/fileexchange/29693-firefly-algorithm] Files of the Matlab programs included in the book: Xin-She Yang, Nature-Inspired Metaheuristic Algorithms, Second Edition, Luniver Press, (2010).


	{{Optimization algorithms}}		{{Optimization algorithms}}

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2023-08-07T06:03:22Z

Alter: title, template type. Add: s2cid, chapter-url, date, chapter. Removed or converted URL. Removed parameters. Some additions/deletions were parameter name changes. | Use this bot. Report bugs. | Suggested by Headbomb | Linked from Wikipedia:WikiProject_Academic_Journals/Journals_cited_by_Wikipedia/Sandbox3 | #UCB_webform_linked 719/2306

← Previous revision		Revision as of 06:03, 7 August 2023
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	== Criticism ==		== Criticism ==

	Nature-inspired [[Metaheuristic\|metaheuristics]] in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite ~~journal~~\|first=Michael A.\|last=Lones~~\|year=2014~~\|title=~~Metaheuristics~~ in ~~Nature-Inspired~~ ~~Algorithms\|journal=[[~~Genetic and Evolutionary Computation ~~Conference~~\|~~GECCO~~ ~~'14]]~~\|pages=1419–1422\|url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825}}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>		Nature-inspired [[Metaheuristic\|metaheuristics]] in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite book\|first=Michael A.\|last=Lones\|title=Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation \|chapter=Metaheuristics in nature-inspired algorithms \|date=2014 \|year=2014\|pages=1419–1422\|chapter-url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825\|s2cid=14997975 }}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>

	==See also==		==See also==

194.167.13.57 at 14:15, 1 June 2023

2023-06-01T14:15:58Z

← Previous revision		Revision as of 14:15, 1 June 2023
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	:: <math>\mathbf{x}_i^{t+1}=\mathbf{x}_i^t + \beta \exp[-\gamma r_{ij}^2] (\mathbf{x}_j^t - \mathbf{x}_i^t) +\alpha_t \boldsymbol{\epsilon}_t </math>		:: <math>\mathbf{x}_i^{t+1}=\mathbf{x}_i^t + \beta \exp[-\gamma r_{ij}^2] (\mathbf{x}_j^t - \mathbf{x}_i^t) +\alpha_t \boldsymbol{\epsilon}_t </math>
	where <math>\alpha_t </math> is a parameter controlling the step size, while <math>\boldsymbol{\epsilon}_t </math> is a vector drawn from a Gaussian or other		where <math>\alpha_t </math> is a parameter controlling the step size, while <math>\boldsymbol{\epsilon}_t </math> is a vector drawn from a Gaussian or other
	distribution.		distribution.zae

	It can be shown that the limiting case <math>\gamma \rightarrow 0 </math> corresponds to the standard [[Particle Swarm Optimization]] (PSO). In fact, if the inner loop (for j) is removed and the brightness <math>I_j</math> is replaced by the current global best <math>g^*</math>, then FA essentially becomes the standard PSO.		It can be shown that the limiting case <math>\gamma \rightarrow 0 </math> corresponds to the standard [[Particle Swarm Optimization]] (PSO). In fact, if the inner loop (for j) is removed and the brightness <math>I_j</math> is replaced by the current global best <math>g^*</math>, then FA essentially becomes the standard PSO.

Triplehuman: removed the word elaborate - the conceopt of a FireFly is not elaborate.

2022-09-29T12:07:34Z

removed the word elaborate - the conceopt of a FireFly is not elaborate.

← Previous revision		Revision as of 12:07, 29 September 2022
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	== Criticism ==		== Criticism ==

	Nature-inspired [[Metaheuristic\|metaheuristics]] in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind ~~an elaborate metaphor~~. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite journal\|first=Michael A.\|last=Lones\|year=2014\|title=Metaheuristics in Nature-Inspired Algorithms\|journal=[[Genetic and Evolutionary Computation Conference\|GECCO '14]]\|pages=1419–1422\|url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825}}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>		Nature-inspired [[Metaheuristic\|metaheuristics]] in general have attracted [[List of metaphor-inspired metaheuristics#Criticism of the metaphor methodology\|criticism in the research community]] for hiding their lack of novelty behind metaphors. The firefly algorithm has been criticized as differing from the well-established [[particle swarm optimization]] only in a negligible way.<ref>{{cite journal\|first1=Omid N.\|last1=Almasi\| first2=Modjtaba\|last2= Rouhani\|year=2016\|title=A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm\|journal=Turkish Journal of Electrical Engineering & Computer Sciences\|volume=4\| pages=1–19\|doi=10.3906/elk-1310-253\|quote= Practical application of FA on UCI datasets.\|doi-access=free}}</ref><ref>{{cite journal\|first=Michael A.\|last=Lones\|year=2014\|title=Metaheuristics in Nature-Inspired Algorithms\|journal=[[Genetic and Evolutionary Computation Conference\|GECCO '14]]\|pages=1419–1422\|url=http://www.macs.hw.ac.uk/~ml355/common/papers/lones-gecco2014-metaheuristics.pdf\|doi=10.1145/2598394.2609841\|quote=FA, on the other hand, has little to distinguish it from PSO, with the inverse-square law having a similar effect to crowding and fitness sharing in EAs, and the use of multi-swarms in PSO.\|isbn=9781450328814\|citeseerx=10.1.1.699.1825}}</ref><ref>{{cite journal\|first=Dennis\|last=Weyland\|year=2015\|title=A critical analysis of the harmony search algorithm—How not to solve sudoku\|journal=Operations Research Perspectives\|volume=2\|pages=97–105\|doi=10.1016/j.orp.2015.04.001\|quote=For example, the differences between the particle swarm optimization metaheuristic and "novel" metaheuristics like the firefly algorithm, the fruit fly optimization algorithm, the fish swarm optimization algorithm or the cat swarm optimization algorithm seem negligible.\|doi-access=free}}</ref>

	==See also==		==See also==

B k: Remove unnecessary/inconsistent line.

2022-04-17T16:18:40Z

Remove unnecessary/inconsistent line.

← Previous revision		Revision as of 16:18, 17 April 2022
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	4) Define absorption coefficient {{mvar\|γ}}		4) Define absorption coefficient {{mvar\|γ}}

	'''~~While~~''' (t < MaxGeneration)		'''while''' (t < MaxGeneration)
	'''for''' i = 1 : n (all n fireflies)		'''for''' i = 1 : n (all n fireflies)
	'''for''' j = 1 : i (n fireflies)		'''for''' j = 1 : i (n fireflies)
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	Rank fireflies and find the current best;		Rank fireflies and find the current best;
	'''end while'''		'''end while'''

	Post-processing the results and visualization;

	'''end'''		'''end'''

2402:4000:2081:958:FC0F:8B44:682A:B3F4: /* References */

2020-10-08T15:02:51Z

References

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	== References ==		== References ==
	{{Reflist\|<ref>A ~~Review~~ of ~~Recent~~ ~~Advancements~~ of ~~Firefly~~ ~~Algorithm;~~ A ~~Modern~~ ~~Nature~~ ~~Inspired~~ ~~Algorithm~~ http://ir.kdu.ac.lk/bitstream/handle/345/1038/com-047.pdf?sequence=1&isAllowed=y</ref>}}		{{Reflist\|<ref>Ariyaratne MKA, Pemarathne WPJ (2015) A review of recent advancements of firefly algorithm: a modern nature inspired algorithm. In: Proceedings of the 8th international research conference, 61–66, KDU, Published November 2015, http://ir.kdu.ac.lk/bitstream/handle/345/1038/com-047.pdf?sequence=1&isAllowed=y</ref>}}

	==External links==		==External links==

2402:4000:2081:958:FC0F:8B44:682A:B3F4: /* References */

2020-10-08T15:01:34Z

References

← Previous revision		Revision as of 15:01, 8 October 2020
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	== References ==		== References ==
	{{Reflist\|A Review of Recent Advancements of Firefly Algorithm; A Modern Nature Inspired Algorithm ~~<ref>~~http://ir.kdu.ac.lk/bitstream/handle/345/1038/com-047.pdf?sequence=1&isAllowed=y</ref>}}		{{Reflist\|<ref>A Review of Recent Advancements of Firefly Algorithm; A Modern Nature Inspired Algorithm http://ir.kdu.ac.lk/bitstream/handle/345/1038/com-047.pdf?sequence=1&isAllowed=y</ref>}}

	==External links==		==External links==

2402:4000:2081:958:FC0F:8B44:682A:B3F4: /* References */

2020-10-08T15:01:04Z

References

← Previous revision		Revision as of 15:01, 8 October 2020
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	== References ==		== References ==
	{{Reflist\|<ref>http://ir.kdu.ac.lk/bitstream/handle/345/1038/com-047.pdf?sequence=1&isAllowed=y</ref>}}		{{Reflist\|A Review of Recent Advancements of Firefly Algorithm; A Modern Nature Inspired Algorithm <ref>http://ir.kdu.ac.lk/bitstream/handle/345/1038/com-047.pdf?sequence=1&isAllowed=y</ref>}}

	==External links==		==External links==