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=== Modified Firefly Algorithm ===
Many variants and modifications are done to increase its performance. A particular example will be modified firefly algorithm by Tilahun and Ong .,<ref>{{cite journal | last1 = Tilahun | first1 = S. L. Tilahun,| last2 = Ong | first2 = H. C. Ong,| year = | title = "Modified Firefly Algorithm, ''| url = | journal = Journal of Applied Mathematics'' | volume = 2012: | issue = | page = 467631 }}</ref> in which the updating process of the brightest firefly is modified to keep the best result throughout the iterations.
== Applications ==
=== Digital Image Compression and Image Processing ===
Very recently, an FF-LBG algorithm for vector quantization of digital image compression was based on the firefly algorithm, which proves to be faster than other algorithms such as [[Particle swarm optimization|PSO]]-LBG and HBMO-LBG (particle swarm optimization and honey-bee mating optimization; variations on the [[Linde–Buzo–Gray algorithm]]).<ref>Horng M.-H. and Jiang T. W., "The codebook design of image vector quantization based on the firefly algorithm, in: ''Computational Collective Intelligence, Technologies and Applications, LNCS,'' Vol. 6423, pp. 438-447 (2010).</ref>
<ref>M.-H. Horng, 2011 vector quantization using the firefly algorithm for image compression, ''Expert Systems with Applications'' Vol. 38:</ref> For minimum cross entropy thresholding, firefly-based algorithm uses the least computation time<ref>{{cite journal | last1 = Horng | first1 = M.-H. Horng| andlast2 = Liou | first2 = R.-J Liou,| year = 2011 | title = Multilevel minimum cross entropy threshold selection based on the firefly algorithm, ''| url = | journal = Expert Systems with Applications'', Vol.| volume = 38, Issue| issue = 12,| 14805-14811pages = 14805–14811 }}</ref> Also, for gel electrophoresis images, FA-based method is very efficient.<ref>M. H. M. Noor, A. R. Ahmad, Z. Hussain, K. A. Ahmad, A. R. Ainihayati, Multilevel thresholding of gel electrophoresis images using firefly algorithm, in: Proceedings of Control System, Computing and Engineering (ICCSCE2011), pp. 18-21 (2011).</ref>
=== Eigenvalue optimization ===
=== Feature selection and fault detection ===
Feature selection can be also carried out successfully using firefly algorithm.<ref>{{cite journal | last1 = Banati | first1 = H. Banati| andlast2 = Bajaj | first2 = M. Bajaj,| year = 2011 | title = Firefly based feature selection approach, ''| url = | journal = Int. J. Computer Science Issues'', vol.| volume = 8, No.| issue = 2,| pages = 473-480473–480 }}</ref> Real-time fault identification in large systems becomes viable, based on the recent work on fault identification with binary adaptive firefly optimization.<ref>R. Falcon, M. Almeida and A. Nayak, Fault identification with binary adaptive fireflies in parallel and distributed systems, IEEE Congress on Evolutionary Computation, (2011).</ref>
A hybrid filter-wrapper feature selection for load forecasting is proposed based on Firefly Algorithm.<ref>{{cite journal | last1 = Hu, | first1 = Z., | last2 = Bao, | first2 = Y., | last3 = Xiong, | first3 = T., &| last4 = Chiong, | first4 = R. (| year = 2015). | title = Hybrid filter–wrapper feature selection for short-term load forecasting. ''| url = | journal = Engineering Applications of Artificial Intelligence'', | volume = 40, 17-27.| issue = | pages = 17–27 }}</ref>
===Antenna Design===
Firefly algorithms outperforms ABC for optimal design of linear array of isotropic sources <ref>{{cite journal | last1 = Basu | first1 = B. Basu| andlast2 = Mahanti | first2 = G. K. Mahanti,| year = 2011 "| title = Firefly and artificial bees colony algorithm for synthesis of scanned and broadside linear array antenna, ''| url = | journal = Progress in Electromagnetic Research B.'', Vol.| volume = 32, 169-190| issue = | pages = 169–190 }}</ref> and digital controllable array antenna.<ref>{{cite journal | last1 = Chatterjee | first1 = A. Chatterjee,| last2 = Mahanti | first2 = G. K. Mahanti,| andlast3 = Chatterjee | first3 = A. Chatterjee,| year = 2012 | title = Design of a fully digital controlled reconfigurable switched beam conconcentric ring array antenna using firefly and particle swarm optimization algorithm, | url = | journal = Progress in Elelectromagnetic Research B, Vol.| volume = 36, 113-131(2012)| issue = | pages = 113–131 }}</ref> It has found applications in synthesis of satellite footprint patterns as well.<ref>Anirban{{cite journal | last1 = Chatterjee, Gautam| first1 = Anirban | last2 = Kumar Mahanti and| Gourabfirst2 = Gautam | last3 = Ghatak, | first3 = Gourab | year = 2014 | title = Synthesis of satellite footprint patterns from rectangular planar array antenna by using swarm-based optimization algorithms, | url = | journal = Int. J. Satell. Commun. Network. 2014;| volume = 32: | issue = | pages = 25–47 }}</ref>
===Structural Design===
For mixed-variable problems, many optimization algorithms may struggle. However, firefly algorithm can efficiently solve optimization problems with mixed variables.<ref>{{cite journal | last1 = Gandomi | first1 = A. H. Gandomi,| last2 = Yang | first2 = X. S. Yang,| last3 = Alavi | first3 = A. H. Alavi,| year = 2011 | title = Mixed variable structural optimization using firefly algorithm, | url = | journal = Computers and Structures, Vol.| volume = 89, No.| issue = 23-24,| pp.pages 2325-2336= (2011).2325–2336 {{doi| doi = 10.1016/j.compstruc.2011.08.002 }}</ref>
=== Scheduling and TSP ===
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