{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T04:29:20Z","timestamp":1781584160994,"version":"3.54.5"},"reference-count":83,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T00:00:00Z","timestamp":1630022400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T00:00:00Z","timestamp":1630022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evol. Intel."],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s12065-021-00659-x","type":"journal-article","created":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T11:03:45Z","timestamp":1630062225000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["A survey on dragonfly algorithm and its applications in engineering"],"prefix":"10.1007","volume":"16","author":[{"given":"Chnoor M.","family":"Rahman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8661-258X","authenticated-orcid":false,"given":"Tarik A.","family":"Rashid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abeer","family":"Alsadoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nebojsa","family":"Bacanin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Polla","family":"Fattah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyedali","family":"Mirjalili","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,8,27]]},"reference":[{"key":"659_CR1","unstructured":"Dorigo., M. Optimization, Learning and Natural Algorithms, 1992. PhD thesis [in Italian], Dipartimento di Elettronica, Politecnico di Milano, Milan, Italy."},{"key":"659_CR2","first-page":"320","volume":"4","author":"E Bonabeau","year":"1999","unstructured":"Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm Intelligence: From Natural to Artificial Systems. J Artif Soc Soc Simul 4:320","journal-title":"J Artif Soc Soc Simul"},{"key":"659_CR3","doi-asserted-by":"publisher","unstructured":"Wahabm Ab, Nefti-Meziani M. S. and Atyabi, A. A Comprehensive Review of Swarm Optimization Algorithms.\u00a0PLOS ONE, 2015, [online] 10(5), p.e0122827. Available at: <https:\/\/journals.plos.org\/plosone\/article?id=https:\/\/doi.org\/10.1371\/journal.pone.0122827> [Accessed 14 March 2020].","DOI":"10.1371\/journal.pone.0122827"},{"key":"659_CR4","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Wang, S. and Ji, G. A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications. Mathematical Problems in Engineering, 2015. [online] Available at: https:\/\/www.hindawi.com\/journals\/mpe\/2015\/931256\/ [Accessed 4 Feb. 2018].","DOI":"10.1155\/2015\/931256"},{"key":"659_CR5","doi-asserted-by":"crossref","unstructured":"Ducatelle, F., Di Caro, G. and Gambardella, L., Principles and applications of swarm intelligence for\u00a0adaptive routing in telecommunications networks.\u00a0Swarm Intelligence, 2010. [online] 4, 3, pp.173\u2013198. Available at: <http:\/\/people.idsia.ch\/~frederick\/sij-submitted.pdf> [Accessed 15 March 2020].","DOI":"10.1007\/s11721-010-0040-x"},{"key":"659_CR6","unstructured":"Kennedy, J. and Eberhart, R. Particle swarm optimization.\u00a0Proceedings of ICNN'95 - International Conference on Neural Networks. 1995. [online] Available at: https:\/\/ieeexplore.ieee.org\/document\/488968 [Accessed 7 Feb. 2018]."},{"issue":"5","key":"659_CR7","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1109\/TEVC.2020.2968743","volume":"24","author":"X Song","year":"2020","unstructured":"Song X, Zhang Y, Guo Y, Sun X, Wang Y (2020) Variable-size cooperative coevolutionary particle swarm optimization for feature selection on high-dimensional data. IEEE Trans Evol Comput 24(5):882\u2013895","journal-title":"IEEE Trans Evol Comput"},{"key":"659_CR8","doi-asserted-by":"crossref","unstructured":"Ji, X., Zhang, Y., Gong, D. and Sun, X., 2021. Dual-Surrogate Assisted Cooperative Particle Swarm Optimization for Expensive Multimodal Problems.\u00a0IEEE Transactions on Evolutionary Computation, pp.1\u20131.","DOI":"10.1109\/TEVC.2022.3182810"},{"issue":"3","key":"659_CR9","doi-asserted-by":"publisher","first-page":"3655","DOI":"10.1007\/s11277-017-4281-5","volume":"96","author":"C Chakraborty","year":"2017","unstructured":"Chakraborty C (2017) Chronic wound image analysis by particle swarm optimization technique for tele-wound network. Wireless Pers Commun 96(3):3655\u20133671","journal-title":"Wireless Pers Commun"},{"key":"659_CR10","doi-asserted-by":"publisher","unstructured":"He, S., Wu, Q. and Saunders, J., .Group Search Optimizer: An Optimization Algorithm Inspired by Animal Searching Behavior.\u00a0IEEE Transactions on Evolutionary Computation, 2009. [online] 13(5), pp.973\u2013990. Available at: <https:\/\/dl.acm.org\/doi\/https:\/\/doi.org\/10.1109\/TEVC.2009.2011992> [Accessed 19 March 2020].","DOI":"10.1109\/TEVC.2009.2011992"},{"key":"659_CR11","doi-asserted-by":"publisher","unstructured":"Gandomi, A., Yang, X. and Alavi, A., Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems.\u00a0Engineering with Computers, 2011. [online] 29(1), pp.17\u201335. Available at: <https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s00366-011-0241-y> [Accessed 19 March 2020].","DOI":"10.1007\/s00366-011-0241-y"},{"key":"659_CR12","doi-asserted-by":"crossref","unstructured":"Mirjalili, S., Mirjalili, S. and Lewis, A. Grey Wolf Optimizer.\u00a0Advances in Engineering Software, 2014. [online] 69, pp.46\u201361. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0965997813001853 [Accessed 3 Jan. 2018].","DOI":"10.1016\/j.advengsoft.2013.12.007"},{"key":"659_CR13","doi-asserted-by":"publisher","unstructured":"Mirjalili, S. Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems.\u00a0Neural Computing and Applications, 2015. [online] 27(4), pp.1053\u20131073. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s00521-015-1920-1 [Accessed 2 Jan. 2018].","DOI":"10.1007\/s00521-015-1920-1"},{"key":"659_CR14","doi-asserted-by":"publisher","unstructured":"Yang, X. Harmony Search as a Metaheuristic Algorithm.\u00a0Music-Inspired Harmony Search Algorithm, 2009. [online] pp.1\u201314. Available at: <https:\/\/link.springer.com\/chapter\/https:\/\/doi.org\/10.1007\/978-3-642-00185-7_1> [Accessed 10 March 2020].","DOI":"10.1007\/978-3-642-00185-7_1"},{"key":"659_CR15","doi-asserted-by":"crossref","unstructured":"Shamsaldin, A., Rashid, T., Al-Rashid Agha, R., Al-Salihi, N. and Mohammadi, M. Donkey and smuggler optimization algorithm: A collaborative working approach to path finding.\u00a0Journal of Computational Design and Engineering, 2019. [online] 6(4), pp.562\u2013583. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2288430018303178 [Accessed 1 May 2019].","DOI":"10.1016\/j.jcde.2019.04.004"},{"key":"659_CR16","doi-asserted-by":"crossref","unstructured":"Yazdani, M. and Jolai, F.. Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm.\u00a0Journal of Computational Design and Engineering, 2016. [online] 3(1), pp.24\u201336. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2288430015000524 [Accessed 8 Mar. 2019].","DOI":"10.1016\/j.jcde.2015.06.003"},{"issue":"2","key":"659_CR17","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.eij.2020.08.003","volume":"22","author":"C Rahman","year":"2021","unstructured":"Rahman C, Rashid T (2021) A new evolutionary algorithm: learner performance based behavior algorithm. Egypt Inform J 22(2):213\u2013223","journal-title":"Egypt Inform J"},{"key":"659_CR18","first-page":"1","volume":"2018","author":"C Dai","year":"2018","unstructured":"Dai C, Lei X (2018) A Decomposition-based multiobjective evolutionary algorithm with adaptive weight adjustment. Complexity 2018:1\u201320","journal-title":"Complexity"},{"key":"659_CR19","doi-asserted-by":"crossref","unstructured":"Rahman, C. and Rashid, T. Dragonfly Algorithm and Its Applications in Applied Science Survey.\u00a0Computational Intelligence and Neuroscience, 2019 [online] 2019, pp.1\u201321. Available at: <https:\/\/www.hindawi.com\/journals\/cin\/2019\/9293617\/> [Accessed 16 March 2020].","DOI":"10.1155\/2019\/9293617"},{"key":"659_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-02141-6","volume-title":"Cuckoo search and firefly algorithm: theory and applications","author":"X Yang","year":"2014","unstructured":"Yang X (2014) Cuckoo search and firefly algorithm: theory and applications. Springer, Cham"},{"key":"659_CR21","doi-asserted-by":"crossref","unstructured":"Reynolds, C. Flocks, herds and schools: A distributed behavioral model.\u00a0Proceedings of the 14th annual conference on Computer graphics and interactive techniques - SIGGRAPH '87, 1987. [online] 21(4), pp.25\u201334. Available at: https:\/\/dl.acm.org\/citation.cfm?id=37406 [Accessed 14 Feb. 2018].","DOI":"10.1145\/37401.37406"},{"key":"659_CR22","doi-asserted-by":"crossref","unstructured":"Ac\u0131, \u00c7. and G\u00fclcan, H. A Modified Dragonfly Optimization Algorithm for Single- and Multiobjective Problems Using Brownian Motion.\u00a0Computational Intelligence and Neuroscience, 2019. [online] 2019, pp.1\u201317. Available at: https:\/\/www.hindawi.com\/journals\/cin\/2019\/6871298\/ [Accessed 21 Sep. 2019].","DOI":"10.1155\/2019\/6871298"},{"key":"659_CR23","doi-asserted-by":"crossref","unstructured":"Mirjalili, S. and Lewis, A. S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization.\u00a0Swarm and Evolutionary Computation, 2013 .[online] 9, pp.1\u201314. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S2210650212000648 [Accessed 14 Feb. 2018].","DOI":"10.1016\/j.swevo.2012.09.002"},{"key":"659_CR24","doi-asserted-by":"crossref","unstructured":"Mafarja, M., Aljarah, I., Heidari, A., Faris, H., Fournier-Viger, P., Li, X. and Mirjalili, S. Binary dragonfly optimization for feature selection using time-varying transfer functions.\u00a0Knowledge-Based Systems, 2018. [online] 161, pp.185\u2013204. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S095070511830399X?via%3Dihub [Accessed 21 Sep. 2019].","DOI":"10.1016\/j.knosys.2018.08.003"},{"key":"659_CR25","doi-asserted-by":"crossref","unstructured":"Mirjalili, S. and Lewis, A. Novel performance metrics for robust multi-objective optimization algorithms.\u00a0Swarm and Evolutionary Computation, 2015. [online] 21, pp.1\u201323. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S2210650214000777 [Accessed 22 Feb. 2018].","DOI":"10.1016\/j.swevo.2014.10.005"},{"key":"659_CR26","doi-asserted-by":"publisher","unstructured":"Coello Coello, C. Evolutionary multi-objective optimization: some current research trends and topics that remain to be explored.\u00a0Frontiers of Computer Science in China, 2009. [online] 3(1), pp.18\u201330. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s11704-009-0005-7 [Accessed 22 Feb. 2018].","DOI":"10.1007\/s11704-009-0005-7"},{"key":"659_CR27","doi-asserted-by":"crossref","unstructured":"Coello Coello, C. and Lechuga, M. MOPSO: a proposal for multiple objective particle swarm optimization.\u00a0Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), 2002. [online] Available at: https:\/\/ieeexplore.ieee.org\/document\/1004388 [Accessed 22 Feb. 2018].","DOI":"10.1109\/CEC.2002.1004388"},{"key":"659_CR28","doi-asserted-by":"crossref","unstructured":"Coello, C., Pulido, G. and Lechuga, M. Handling multiple objectives with particle swarm optimization.\u00a0IEEE Transactions on Evolutionary Computation, 2004. [online] 8(3), pp.256\u2013279. Available at: https:\/\/ieeexplore.ieee.org\/document\/1304847 [Accessed 9 Mar. 2018].","DOI":"10.1109\/TEVC.2004.826067"},{"key":"659_CR29","doi-asserted-by":"crossref","unstructured":"Li, J., Lu, J., Yao, L., Cheng, L. and Qin, H. (2019). Wind-Solar-Hydro power optimal scheduling model based on multi-objective dragonfly algorithm.\u00a0Energy Procedia, [online] 158, pp.6217\u20136224. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1876610219304990 [Accessed 21 Sep. 2019].","DOI":"10.1016\/j.egypro.2019.01.476"},{"key":"659_CR30","unstructured":"Zitzler E, Laumanns M, Thiele L. (2001). SPEA2: Improving the strength pareto evolutionary algorithm.\u00a0TIK-Report, [online] 103, pp.95\u2013100. Available at: <https:\/\/www.research-collection.ethz.ch\/handle\/20.500.11850\/145755> [Accessed 18 June 2021]."},{"key":"659_CR31","doi-asserted-by":"crossref","unstructured":"Deb, K. and Jain, H. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints.\u00a0IEEE Transactions on Evolutionary Computation, 2014. [online] 18(4), pp.577\u2013601. Available at: https:\/\/ieeexplore.ieee.org\/document\/6600851 [Accessed 25 Nov. 2019].","DOI":"10.1109\/TEVC.2013.2281535"},{"key":"659_CR32","doi-asserted-by":"crossref","unstructured":"K.S., S. and Murugan, S. Memory based Hybrid Dragonfly Algorithm for numerical optimization problems.\u00a0Expert Systems with Applications, 2017. [online] 83, pp.63\u201378. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417417302762 [Accessed 9 Mar. 2018].","DOI":"10.1016\/j.eswa.2017.04.033"},{"key":"659_CR33","unstructured":"Xu, J. and Yan, F. Hybrid Nelder\u2013Mead Algorithm and Dragonfly Algorithm for Function Optimization and the Training of a Multilayer Perceptron.\u00a0Arabian Journal for Science and Engineering, 2018. [online] Available at: https:\/\/link.springer.com\/article\/10.1007%2Fs13369-018-3536-0 [Accessed 2 Mar. 2019]."},{"key":"659_CR34","doi-asserted-by":"publisher","unstructured":"Ghanem, W. and Jantan, A. A Cognitively Inspired Hybridization of Artificial Bee Colony and Dragonfly Algorithms for Training Multi-layer Perceptrons.\u00a0Cognitive Computation, 2018. [online] 10(6), pp.1096\u20131134. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s12559-018-9588-3 [Accessed 12 Mar. 2019].","DOI":"10.1007\/s12559-018-9588-3"},{"key":"659_CR35","doi-asserted-by":"publisher","unstructured":"Yuan, Y., Lv, L., Wang, X. and Song, X. Optimization of a frame structure using the Coulomb force search strategy-based dragonfly algorithm.\u00a0Engineering Optimization, 2019. [online] pp.1\u201317. Available at: https:\/\/www.tandfonline.com\/doi\/full\/https:\/\/doi.org\/10.1080\/0305215X.2019.1618290 [Accessed 21 Sep. 2019].","DOI":"10.1080\/0305215X.2019.1618290"},{"key":"659_CR36","doi-asserted-by":"crossref","unstructured":"K., T. and Aravindhababu, P. Dragonfly Optimization based Reconfiguration for Voltage Profile Enhancement in Distribution Systems.\u00a0International Journal of Computer Applications, 2017. [online] 158(3), pp.1\u20134. Available at: https:\/\/www.semanticscholar.org\/paper\/Dragonfly-Optimization-based-Reconfiguration-for-in Abhiraj\/6970179fb3b97a55dc881e8aa1c42e4dac44dc5d [Accessed 11 Mar. 2018].","DOI":"10.5120\/ijca2017912758"},{"key":"659_CR37","doi-asserted-by":"crossref","unstructured":"Andervazh, M., Haghifam, M. and Olamaei, J. Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory.\u00a0IET Generation, Transmission & Distribution, 2013. [online] 7(12), pp.1367\u20131382. Available at: https:\/\/ieeexplore.ieee.org\/document\/6674159 [Accessed 11 Mar. 2018].","DOI":"10.1049\/iet-gtd.2012.0712"},{"key":"659_CR38","doi-asserted-by":"crossref","unstructured":"Gupta, N., Swarnkar, A. and Niazi, K. Distribution network reconfiguration for power quality and reliability improvement using Genetic Algorithms.\u00a0International Journal of Electrical Power & Energy Systems, 2014 [online] 54, pp.664\u2013671. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0142061513003578 [Accessed 11 Mar. 2018].","DOI":"10.1016\/j.ijepes.2013.08.016"},{"key":"659_CR39","doi-asserted-by":"crossref","unstructured":"Aruul, S. and Santhi, R. New Reconfiguration Method for Improving Voltage Profile of Distribution Networks.\u00a0International Journal of Computer Applications, 2016. [online] 135(7), pp.25\u201329. Available at: https:\/\/www.semanticscholar.org\/paper\/New-Reconfiguration-Method-for-Improving-Voltage-of-Santhi-Jabr\/382de46c554feb5d53a550579f7aa48af9ddd6ce [Accessed 11 Mar. 2018].","DOI":"10.5120\/ijca2016908460"},{"key":"659_CR40","unstructured":"Algabalawy, M., Mekhamer, S. and Abdelaziz, A. Optimal Design of a New Configuration of the Distributed Generation Units using Grey Wolf and Dragonfly Optimizers. MASK International Journal of Science and Technology. 2017. [online] 2(1). Available at: https:\/\/www.academia.edu\/31230265\/Optimal_Design_of_a_New_Configuration_of_the_Distributed_Generation_Units_using_Grey_Wolf_and_Dragonfly_Optimizers. [Accessed 11 Mar. 2018]."},{"key":"659_CR41","doi-asserted-by":"crossref","unstructured":"Jafari, M. and Bayati Chaleshtari, M. Using dragonfly algorithm for optimization of orthotropic infinite plates with a quasi-triangular cut-out.\u00a0European Journal of Mechanics - A\/Solids, 2017. [online] 66, pp.1\u201314. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0997753817304370 [Accessed 12 Feb. 2019].","DOI":"10.1016\/j.euromechsol.2017.06.003"},{"key":"659_CR42","doi-asserted-by":"crossref","unstructured":"Bloomfield, M., Herencia, J. and Weaver, P. Analysis and benchmarking of meta-heuristic techniques for lay-up optimization.\u00a0Computers & Structures, 2010 [online] 88(5\u20136), pp.272\u2013282. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0045794909002648 [Accessed 12 Feb. 2019].","DOI":"10.1016\/j.compstruc.2009.10.007"},{"key":"659_CR43","doi-asserted-by":"publisher","unstructured":"Babayigit, B. Synthesis of concentric circular antenna arrays using dragonfly algorithm.\u00a0International Journal of Electronics, 2017. [online] 105(5), pp.784\u2013793. Available at: https:\/\/doi.org\/10.1080\/00207217.2017.1407964 [Accessed 13 Feb. 2019].","DOI":"10.1080\/00207217.2017.1407964"},{"key":"659_CR44","doi-asserted-by":"crossref","unstructured":"Bloomfield, M., Herencia, J. and Weaver, P. Analysis and benchmarking of meta-heuristic techniques for lay-up optimization.\u00a0Computers & Structures, 2020. [online] 88(5\u20136), pp.272\u2013282. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0045794909002648 [Accessed 12 Feb. 2019].","DOI":"10.1016\/j.compstruc.2009.10.007"},{"key":"659_CR45","doi-asserted-by":"publisher","unstructured":"Dib, N. (2017). Design of planar concentric circular antenna arrays with reduced side lobe level using symbiotic organisms search.\u00a0Neural Computing and Applications, [online] 30(12), pp.3859\u20133868. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s00521-017-2971-2 [Accessed 13 Feb. 2019].","DOI":"10.1007\/s00521-017-2971-2"},{"key":"659_CR46","doi-asserted-by":"publisher","unstructured":"Ram, G., Mandal, D., Kar, R. and Ghoshal, S. Circular and Concentric Circular Antenna Array Synthesis Using Cat Swarm Optimization.\u00a0IETE Technical Review, 2015. [online] 32(3), pp.204\u2013217. Available at: https:\/\/www.tandfonline.com\/doi\/abs\/https:\/\/doi.org\/10.1080\/02564602.2014.1002543?journalCode=titr20 [Accessed 14 Feb. 2019]","DOI":"10.1080\/02564602.2014.1002543?journalCode=titr20"},{"key":"659_CR47","unstructured":"Ram, G., Mandal, D., Kar, R. and Prasad Ghoshal, S. Opposition-based gravitational search algorithm for synthesis circular and concentric circular antenna arrays.\u00a0scientia Iranica, 2015.[online] 22(6). Available at: http:\/\/scientiairanica.sharif.edu\/article_3796_e57ae2fe002d2736cf943f020f5ac2fc.pdf [Accessed 14 Feb. 2019]."},{"key":"659_CR48","doi-asserted-by":"publisher","unstructured":"Mandal, D., Ghoshal, S. and Bhattacharjee, A. Design of Concentric Circular Antenna Array with Central Element Feeding Using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach and Evolutionary Programing Technique.\u00a0Journal of Infrared, Millimeter, and Terahertz Waves, 2010. [online] 31(6), pp.667\u2013680. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s10762-010-9629-9 [Accessed 14 Feb. 2019].","DOI":"10.1007\/s10762-010-9629-9"},{"key":"659_CR49","doi-asserted-by":"publisher","unstructured":"Sharaqa, A. and Dib, N. Circular antenna array synthesis using firefly algorithm.\u00a0International Journal of RF and Microwave Computer-Aided Engineering, 2013. [online] 24(2), pp.139\u2013146. Available at: https:\/\/onlinelibrary.wiley.com\/doi\/abs\/https:\/\/doi.org\/10.1002\/mmce.20721 [Accessed 15 Feb. 2019].","DOI":"10.1002\/mmce.20721"},{"key":"659_CR50","doi-asserted-by":"publisher","unstructured":"Simhadri, K., Mohanty, B. and Mohan Rao, U. (2018). Optimized 2DOF PID for AGC of Multi-area Power System Using Dragonfly Algorithm.\u00a0Advances in Intelligent Systems and Computing, 2018. [online] pp.11\u201322. Available at: https:\/\/link.springer.com\/chapter\/https:\/\/doi.org\/10.1007\/978-981-13-1819-1_2 [Accessed 20 Feb. 2019].","DOI":"10.1007\/978-981-13-1819-1_2"},{"key":"659_CR51","doi-asserted-by":"publisher","unstructured":"Khalilpourazari, S. and Khalilpourazary, S. Optimization of time, cost and surface roughness in grinding process using a robust multi-objective dragonfly algorithm.\u00a0Neural Computing and Applications, 2018 [online] pp.1\u201312. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s00521-018-3872-8 [Accessed 19 Feb. 2019].","DOI":"10.1007\/s00521-018-3872-8"},{"key":"659_CR52","doi-asserted-by":"publisher","unstructured":"Gholami, M. and Azizi, M. Constrained grinding optimization for time, cost, and surface roughness using NSGA-II.\u00a0The International Journal of Advanced Manufacturing Technology, 2014.[online] 73(5\u20138), pp.981\u2013988. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s00170-014-5884-6 [Accessed 20 Feb. 2019].","DOI":"10.1007\/s00170-014-5884-6"},{"key":"659_CR53","unstructured":"El-Hay, E., El-Hameed, M. and El-Fergany, A. Improved performance of PEM fuel cells stack feeding switched reluctance motor using multi-objective dragonfly optimizer.\u00a0Neural Computing and Applications, 2018. [online] Available at: https:\/\/link.springer.com\/article\/10.1007%2Fs00521-018-3524-z [Accessed 21 Sep. 2019]."},{"key":"659_CR54","doi-asserted-by":"crossref","unstructured":"Amroune, M., Bouktir, T. and Musirin, I.. Power System Voltage Stability Assessment Using a Hybrid Approach Combining Dragonfly Optimization Algorithm and Support Vector Regression.\u00a0Arabian Journal for Science and Engineering, 2018. [online] 43(6), pp.3023\u20133036. Available at: https:\/\/link.springer.com\/article\/10.1007%2Fs13369-017-3046-5 [Accessed 21 Sep. 2019].","DOI":"10.1007\/s13369-017-3046-5"},{"key":"659_CR55","doi-asserted-by":"crossref","unstructured":"Guha, K., Laskar, N., Gogoi, H., Borah, A., Baishnab, K. and Baishya, S. Novel analytical model for optimizing the pull-in voltage in a flexured MEMS switch incorporating beam perforation effect.\u00a0Solid-State Electronics, 2017. [online] 137, pp.85\u201394. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0038110117300229 [Accessed 14 Apr. 2018].","DOI":"10.1016\/j.sse.2017.08.007"},{"key":"659_CR56","unstructured":"Vanishree, J. and Ramesh, V. Optimization of size and cost of static var compensator using dragonfly algorithm for voltage profile improvement in power transmission systems.\u00a0International Journal of Renewable Energy Research (IJRER), 2017. [online] 8(1), pp.56\u201366. Available at: https:\/\/ijrer.org\/ijrer\/index.php\/ijrer\/article\/view\/6933 [Accessed 20 Feb. 2019]."},{"key":"659_CR57","doi-asserted-by":"publisher","unstructured":"Kouba, N., Menaa, M., Hasni, M. and Boudour, M. A Novel Optimal Combined Fuzzy PID Controller Employing Dragonfly Algorithm for Solving Automatic Generation Control Problem.\u00a0Electric Power Components and Systems, 2018. [online] pp.1\u201317. Available at: https:\/\/www.tandfonline.com\/doi\/abs\/https:\/\/doi.org\/10.1080\/15325008.2018.1533604?af=R&journalCode=uemp20 [Accessed 23 Feb. 2019].","DOI":"10.1080\/15325008.2018.1533604?af=R&journalCode=uemp20"},{"key":"659_CR58","doi-asserted-by":"crossref","unstructured":"Jafari, M. and Bayati Chaleshtari, M. Using dragonfly algorithm for optimization of orthotropic infinite plates with a quasi-triangular cut-out.\u00a0European Journal of Mechanics - A\/Solids, 2017. [online] 66, pp.1\u201314. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0997753817304370 [Accessed 2 Mar. 2018].","DOI":"10.1016\/j.euromechsol.2017.06.003"},{"key":"659_CR59","unstructured":"Mathworks.com. Genetic Algorithm. 2018. [online] Available at: https:\/\/www.mathworks.com\/discovery\/genetic-algorithm.html [Accessed 27 May 2018]."},{"key":"659_CR60","doi-asserted-by":"crossref","unstructured":"Bhesdadiya, R., Pandya, M., Trivedi, I., Jangir, N., Jangir, P. and Kumar, A. Price penalty factors based approach for combined economic emission dispatch problem solution using Dragonfly Algorithm. International Conference on Energy Efficient Technologies for Sustainability (ICEETS), 2016. [online] Available at: https:\/\/ieeexplore.ieee.org\/document\/7583794 [Accessed 1 Mar. 2018].","DOI":"10.1109\/ICEETS.2016.7583794"},{"key":"659_CR61","doi-asserted-by":"crossref","unstructured":"Guo, S., Dooner, M., Wang, J., Xu, H. and Lu, G. Adaptive engine optimisation using NSGA-II and MODA based on a sub-structured artificial neural network.\u00a02017 23rd International Conference on Automation and Computing (ICAC), 2017. [online] Available at: https:\/\/ieeexplore.ieee.org\/document\/8082008 [Accessed 15 Feb. 2019].","DOI":"10.23919\/IConAC.2017.8082008"},{"key":"659_CR62","doi-asserted-by":"crossref","unstructured":"Guha, D., Roy, P. and Banerjee, S. Optimal tuning of 3 degree-of-freedom proportional-integral-derivative controller for hybrid distributed power system using dragonfly algorithm.\u00a0Computers & Electrical Engineering, 2018. [online] 72, pp.137\u2013153. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0045790618304609 [Accessed 19 Feb. 2019].","DOI":"10.1016\/j.compeleceng.2018.09.003"},{"key":"659_CR63","doi-asserted-by":"crossref","unstructured":"Pathania, A., Mehta, S. and Rza, C. Economic load dispatch of wind thermal integrated system using dragonfly algorithm.\u00a02016 7th India International Conference on Power Electronics (IICPE). 2016. [online] Available at: https:\/\/ieeexplore.ieee.org\/document\/8079422 [Accessed 14 Apr. 2018].","DOI":"10.1109\/IICPE.2016.8079422"},{"key":"659_CR64","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Yao, F., Iu, H., Fernando, T. and Wong, K. Sequential quadratic programming particle swarm optimization for wind power system operations considering emissions.\u00a0Journal of Modern Power Systems and Clean Energy, 2013. [online] 1(3), pp.231\u2013240. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s40565-013-0030-2 [Accessed 14 Apr. 2018].","DOI":"10.1007\/s40565-013-0030-2"},{"key":"659_CR65","doi-asserted-by":"publisher","unstructured":"Suresh, V. and Sreejith, S. Generation dispatch of combined solar thermal systems using dragonfly algorithm.\u00a0Computing, 2016. [online] 99(1), pp.59\u201380. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s00607-016-0514-9 [Accessed 16 May 2018].","DOI":"10.1007\/s00607-016-0514-9"},{"key":"659_CR66","doi-asserted-by":"crossref","unstructured":"Mafarja, M., Eleyan, D., Jaber, I., Hammouri, A. and Mirjalili, S. Binary Dragonfly Algorithm for Feature Selection.\u00a02017 International Conference on New Trends in Computing Sciences (ICTCS), 2017. [online] Available at: https:\/\/ieeexplore.ieee.org\/document\/8250257 [Accessed 10 May 2018].","DOI":"10.1109\/ICTCS.2017.43"},{"key":"659_CR67","doi-asserted-by":"crossref","unstructured":"Emary, E., Zawbaa, H. and Hassanien, A. Binary ant lion approaches for feature selection. Neurocomputing, 2016. online] 213, pp.54\u201365. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0925231216307263 [Accessed 2 Jul. 2018].","DOI":"10.1016\/j.neucom.2016.03.101"},{"key":"659_CR68","doi-asserted-by":"crossref","unstructured":"Hamdy, M., Nguyen, A. and Hensen, J. A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems.\u00a0Energy and Buildings, 2016. [online] 121, pp.57\u201371. Available at: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0378778816301724 [Accessed 1 Mar. 2018].","DOI":"10.1016\/j.enbuild.2016.03.035"},{"key":"659_CR69","doi-asserted-by":"crossref","unstructured":"Arulraj, R. and Kumarappan, N. Simultaneous Multiple DG and Capacitor Installation Using Dragonfly Algorithm for Loss Reduction and Loadability Improvement in Distribution System.\u00a02018 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), 2018. [online] Available at: https:\/\/ieeexplore.ieee.org\/xpl\/mostRecentIssue.jsp?punumber=8501352&filter=issueId%20EQ%20%228521560%22&pageNumber=2 [Accessed 19 Feb. 2019].","DOI":"10.1109\/ICPECTS.2018.8521605"},{"key":"659_CR70","doi-asserted-by":"publisher","unstructured":"Wongsinlatam, W. and Buchitchon, S. The Comparison between Dragonflies Algorithm and Fireflies Algorithm for Court Case Administration: a Mixed Integer Linear Programming.\u00a0Journal of Physics: Conference Series, 2018, [online] 1061, p.012005. Available at: https:\/\/iopscience.iop.org\/article\/https:\/\/doi.org\/10.1088\/1742-6596\/1061\/1\/012005 [Accessed 23 Feb. 2019].","DOI":"10.1088\/1742-6596\/1061\/1\/012005"},{"key":"659_CR71","doi-asserted-by":"publisher","unstructured":"Diab, A. and Rezk, H. Optimal Sizing and Placement of Capacitors in Radial Distribution Systems Based on Grey Wolf, Dragonfly and Moth\u2013Flame Optimization Algorithms.\u00a0Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2018, [online] 43(1), pp.77\u201396. Available at: https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s40998-018-0071-7 [Accessed 24 Feb. 2019].","DOI":"10.1007\/s40998-018-0071-7"},{"key":"659_CR72","doi-asserted-by":"crossref","unstructured":"Al-Madi, N., Faris, H. and Mirjalili, S.. Binary multi-verse optimization algorithm for global optimization and discrete problems.\u00a0International Journal of Machine Learning and Cybernetics. 2019, [online] Available at: https:\/\/www.springerprofessional.de\/en\/binary-multi-verse-optimization-algorithm-for-global-optimizatio\/16442930 [Accessed 21 Sep. 2019].","DOI":"10.1007\/s13042-019-00931-8"},{"key":"659_CR73","unstructured":"Moayedi, H., Abdullahi, M., Nguyen, H. and Rashid, A. Comparison of dragonfly algorithm and Harris hawks optimization evolutionary data mining techniques for the assessment of bearing capacity of footings over two-layer foundation soils.\u00a0Engineering with Computers, (2019), [online] pp.1\u201311. Available at: https:\/\/link.springer.com\/article\/10.1007%2Fs00366-019-00834-w [Accessed 21 Sep. 2019]."},{"key":"659_CR74","volume-title":"The 100-digit challenge: problem definitions and evaluation criteria for the 100-digit challenge special session and competition on single objective numerical optimization","author":"KV Price","year":"2018","unstructured":"Price KV, Awad NH, Ali MZ, Suganthan PN (2018) The 100-digit challenge: problem definitions and evaluation criteria for the 100-digit challenge special session and competition on single objective numerical optimization. Nanyang Technological University, Singapore"},{"key":"659_CR75","doi-asserted-by":"crossref","unstructured":"Mirjalili, S. and Lewis, A. S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization.\u00a0Swarm and Evolutionary Computation, 2013. [online] 9, pp.1\u201314. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S2210650212000648 [Accessed 2 Mar. 2019].","DOI":"10.1016\/j.swevo.2012.09.002"},{"key":"659_CR76","doi-asserted-by":"crossref","unstructured":"Ma, H., Simon, D., Fei, M., Shu, X. and Chen, Z. Hybrid biogeography-based evolutionary algorithms.\u00a0Engineering Applications of Artificial Intelligence, 2014. [online] 30, pp.213\u2013224. Available at: https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0952197614000189 [Accessed 5 Mar. 2018].","DOI":"10.1016\/j.engappai.2014.01.011"},{"key":"659_CR77","doi-asserted-by":"crossref","unstructured":"Tejani, G., Savsani, V. and Patel, V. Adaptive symbiotic organisms search (SOS) algorithm for structural design optimization.\u00a0Journal of Computational Design and Engineering, 2016. [online] 3(3), pp.226\u2013249. Available at: https:\/\/www.scopus.com\/record\/display.uri?eid=2-s2.0-84991722784&origin=inward&txGid=94c67ebb12be33b0fb72098991bc1ffc [Accessed 24 Nov. 2019].","DOI":"10.1016\/j.jcde.2016.02.003"},{"key":"659_CR78","doi-asserted-by":"crossref","unstructured":"Sayed, G., Tharwat, A. and Hassanien, A. Chaotic dragonfly algorithm: an improved metaheuristic algorithm for feature selection.\u00a0Applied Intelligence, 2019. [online] 49(1), pp.188\u2013205. Available at: https:\/\/link.springer.com\/article\/10.1007%2Fs10489-018-1261-8.","DOI":"10.1007\/s10489-018-1261-8"},{"issue":"1","key":"659_CR79","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1016\/j.eswa.2009.05.045","volume":"37","author":"MRSCCA KrishnanMBanerjeeChakrabortyChakrab","year":"2010","unstructured":"KrishnanMBanerjeeChakrabortyChakrabortyRay MRSCCA (2010) Statistical analysis of mammographic features and its classification using support vector machine. Expert Syst Appl 37(1):470\u2013478","journal-title":"Expert Syst Appl"},{"issue":"1","key":"659_CR80","doi-asserted-by":"publisher","first-page":"76","DOI":"10.4018\/IJEHMC.2016010105","volume":"7","author":"C Chakraborty","year":"2016","unstructured":"Chakraborty C, Gupta B, Ghosh S (2016) Chronic wound characterization using bayesian classifier under telemedicine framework. Int J E-Health Med Commun 7(1):76\u201393","journal-title":"Int J E-Health Med Commun"},{"key":"659_CR81","doi-asserted-by":"crossref","unstructured":"Mohammed, H., Umar, S. and Rashid, T. A Systematic and Meta-Analysis Survey of Whale Optimization Algorithm.\u00a0Computational Intelligence and Neuroscience, 2019. [online] 2019, pp.1\u201325. Available at: https:\/\/www.hindawi.com\/journals\/cin\/2019\/8718571\/ [Accessed 14 Dec. 2019].","DOI":"10.1155\/2019\/8718571"},{"key":"659_CR82","doi-asserted-by":"crossref","unstructured":"Abdullah, J. and Ahmed, T. Fitness Dependent Optimizer: Inspired by the Bee Swarming Reproductive Process.\u00a0IEEE Access, 2019. [online] 7, pp.43473\u201343486. Available at: https:\/\/ieeexplore.ieee.org\/document\/8672851 [Accessed 14 Dec. 2019].","DOI":"10.1109\/ACCESS.2019.2907012"},{"key":"659_CR83","doi-asserted-by":"publisher","unstructured":"Rashid, T., Abbas, D. and Turel, Y. A multi hidden recurrent neural network with a modified grey wolf optimizer.\u00a0PLOS ONE, 2019. [online] 14(3), p.e0213237. Available at: https:\/\/journals.plos.org\/plosone\/article?id=https:\/\/doi.org\/10.1371\/journal.pone.0213237 [Accessed 14 Dec. 2019]","DOI":"10.1371\/journal.pone.0213237"}],"container-title":["Evolutionary Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12065-021-00659-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12065-021-00659-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12065-021-00659-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T05:39:14Z","timestamp":1725687554000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12065-021-00659-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,27]]},"references-count":83,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["659"],"URL":"https:\/\/doi.org\/10.1007\/s12065-021-00659-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.11811768.v1","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.11811768.v2","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.11811768.v3","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.11811768","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.11811768.v4","asserted-by":"object"}]},"ISSN":["1864-5909","1864-5917"],"issn-type":[{"value":"1864-5909","type":"print"},{"value":"1864-5917","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,27]]},"assertion":[{"value":"5 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 July 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 August 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 August 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}]}}