Lotus effect optimization algorithm (LEA): a lotus nature-inspired algorithm for engineering design optimization

Here we introduce a new evolutionary algorithm called the Lotus Effect Algorithm, which combines efficient operators from the dragonfly algorithm, such as the movement of dragonflies in flower pollination for exploration, with the self-cleaning feature of water on flower leaves known as the lotus ef...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	The Journal of supercomputing Ročník 80; číslo 1; s. 761 - 799
Hlavní autoři:	Dalirinia, Elham, Jalali, Mehrdad, Yaghoobi, Mahdi, Tabatabaee, Hamid
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.01.2024 Springer Nature B.V
Témata:	Accuracy Benchmarks Biogeography Clustering Compilers Computer Science Data transmission Design engineering Design optimization Energy consumption Energy efficiency Evolutionary algorithms Flowers Heuristic Internet of Things Interpreters Optimization algorithms Optimization techniques Performance evaluation Processor Architectures Productivity Programming Languages Sensors Wireless networks Network clustering Internet of Things (IoT) Evolutionary algorithms Lotus effect Dragonfly algorithm Optimization
ISSN:	0920-8542, 1573-0484
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	Here we introduce a new evolutionary algorithm called the Lotus Effect Algorithm, which combines efficient operators from the dragonfly algorithm, such as the movement of dragonflies in flower pollination for exploration, with the self-cleaning feature of water on flower leaves known as the lotus effect, for extraction and local search operations. The authors compared this method to other improved versions of the dragonfly algorithm using standard benchmark functions, and it outperformed all other methods according to Fredman's test on 29 benchmark functions. The article also highlights the practical application of LEA in reducing energy consumption in IoT nodes through clustering, resulting in increased packet delivery ratio and network lifetime. Additionally, the performance of the proposed method was tested on real-world problems with multiple constraints, such as the welded beam design optimization problem and the speed-reducer problem applied in a gearbox, and the results showed that LEA performs better than other methods in terms of accuracy.
AbstractList	Here we introduce a new evolutionary algorithm called the Lotus Effect Algorithm, which combines efficient operators from the dragonfly algorithm, such as the movement of dragonflies in flower pollination for exploration, with the self-cleaning feature of water on flower leaves known as the lotus effect, for extraction and local search operations. The authors compared this method to other improved versions of the dragonfly algorithm using standard benchmark functions, and it outperformed all other methods according to Fredman's test on 29 benchmark functions. The article also highlights the practical application of LEA in reducing energy consumption in IoT nodes through clustering, resulting in increased packet delivery ratio and network lifetime. Additionally, the performance of the proposed method was tested on real-world problems with multiple constraints, such as the welded beam design optimization problem and the speed-reducer problem applied in a gearbox, and the results showed that LEA performs better than other methods in terms of accuracy.
Author	Jalali, Mehrdad Tabatabaee, Hamid Dalirinia, Elham Yaghoobi, Mahdi
Author_xml	– sequence: 1 givenname: Elham surname: Dalirinia fullname: Dalirinia, Elham organization: Department of Computer Engineering, Mashhad Branch, Islamic Azad University – sequence: 2 givenname: Mehrdad surname: Jalali fullname: Jalali, Mehrdad email: mehrdad.jalali@kit.edu organization: Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Institute of Functional Interfaces, Karlsruhe Institute of Technology (KIT) – sequence: 3 givenname: Mahdi surname: Yaghoobi fullname: Yaghoobi, Mahdi organization: Department of Electrical Engineering, Mashhad Branch, Islamic Azad University – sequence: 4 givenname: Hamid surname: Tabatabaee fullname: Tabatabaee, Hamid organization: Department of Computer Engineering, Mashhad Branch, Islamic Azad University
BookMark	eNp9kEtLAzEQx4Mo2Fa_gKcFL3pYzWPTpN5KqQ8oeNFzyG4ma0qbrEl60E_vthV8HHoaBv6Pmd8QHfvgAaELgm8IxuI2EUKpKDFlJeacsFIeoQHhol8rWR2jAZ5QXEpe0VM0TGmJMa6YYAPULULepAKshSYXoctu7T51dsEXetWG6PLburhazKfXd4UuVjux13kToXQ-dS6C-SW0IRbgW-cBovNtYSC51v-JPUMnVq8SnH_PEXq9n7_MHsvF88PTbLooGzZmudRWG1xXHDd2LAypsaAGBK8qYxglYPqvtZUCxnUlGwJgpcVSMEOMtLWUko3Q5T63i-F9AymrZdhE31cqRvmYywmlvFfJvaqJIaUIVjUu7-7MUbuVIlht-ao9X9XzVTu-altA_1m76NY6fhw2sb0pdVtAEH-uOuD6AoE9kaM
CitedBy_id	crossref_primary_10_1016_j_advengsoft_2024_103862 crossref_primary_10_1038_s41598_024_55040_6 crossref_primary_10_1007_s11760_025_03899_x crossref_primary_10_1038_s41598_025_96559_6 crossref_primary_10_1016_j_asoc_2025_113870 crossref_primary_10_1007_s00202_024_02591_6 crossref_primary_10_1007_s10707_025_00550_2 crossref_primary_10_1080_0954898X_2024_2339477 crossref_primary_10_1007_s12065_024_00937_4 crossref_primary_10_1038_s41598_025_07328_4 crossref_primary_10_3390_su17062744 crossref_primary_10_1186_s40537_025_01220_8 crossref_primary_10_1016_j_egyr_2025_08_007 crossref_primary_10_1007_s00202_024_02897_5 crossref_primary_10_1007_s12008_024_02174_6 crossref_primary_10_1016_j_compeleceng_2025_110315 crossref_primary_10_1016_j_csite_2025_106437 crossref_primary_10_1016_j_heliyon_2024_e34050 crossref_primary_10_1007_s12008_024_02158_6 crossref_primary_10_1016_j_bspc_2025_108200 crossref_primary_10_1016_j_mtcomm_2025_113842 crossref_primary_10_1080_03772063_2025_2505111 crossref_primary_10_1142_S0219876225500112 crossref_primary_10_1016_j_est_2025_117880 crossref_primary_10_3103_S8756699025700177 crossref_primary_10_3390_w17020234 crossref_primary_10_1007_s44163_025_00367_w crossref_primary_10_1016_j_energy_2025_136929 crossref_primary_10_1007_s10586_024_04950_1 crossref_primary_10_1016_j_measurement_2025_118361 crossref_primary_10_1007_s11760_025_04559_w crossref_primary_10_1007_s11227_024_06291_7 crossref_primary_10_1007_s44443_025_00139_7 crossref_primary_10_1016_j_eij_2025_100623 crossref_primary_10_1109_ACCESS_2024_3406749 crossref_primary_10_1016_j_iot_2025_101593 crossref_primary_10_1007_s10668_025_06449_0 crossref_primary_10_1007_s00521_024_10346_4 crossref_primary_10_3390_biomimetics10060379 crossref_primary_10_32604_cmc_2024_055561 crossref_primary_10_1038_s41598_025_90000_8 crossref_primary_10_1108_WJE_02_2025_0110
Cites_doi	10.1007/s00500-020-05340-6 10.1016/j.comcom.2008.12.045 10.1007/978-3-642-32894-7_27 10.1016/j.enconman.2023.116938 10.1109/ICIMIA48430.2020.9074912 10.1016/j.cie.2021.107408 10.3390/s23083833 10.1016/j.asoc.2008.04.016 10.1109/ACCESS.2019.2893501 10.1007/s00366-020-00958-4 10.1038/s41598-022-14338-z 10.1016/j.advengsoft.2016.01.008 10.1016/j.eswa.2021.115665 10.1890/08-0153.1 10.1007/978-981-19-3571-8_40 10.1109/ICRCICN.2016.7813643 10.1021/acs.langmuir.5b00670 10.1016/j.procs.2017.12.034 10.1016/j.matcom.2020.06.012 10.1109/SIS.2005.1501605 10.1049/iet-com.2019.1311 10.1109/IMICPW.2019.8933284 10.47277/IJCNCS/8(2)2 10.1109/ACCESS.2018.2885539 10.1007/s11227-022-04959-6 10.1007/978-981-13-9282-5_51 10.1109/CSPA.2019.8695973 10.1016/j.cma.2021.114194 10.1007/s13369-022-06880-9 10.1007/s11276-017-1468-3 10.1109/IBCAST.2017.7868141 10.1016/j.ijleo.2016.04.041 10.1007/s10489-020-01893-z 10.3390/infrastructures7040046 10.1109/JSEN.2018.2869629 10.1006/anbo.1997.0400 10.1016/j.epsr.2023.109351 10.1007/978-981-13-9330-3_18 10.1007/s12652-017-0614-1 10.3390/app10144795 10.1016/j.matcom.2022.06.007 10.1109/Confluence47617.2020.9058312 10.1007/s10462-022-10173-w 10.1038/s41598-022-27344-y 10.1155/2019/6871298 10.1007/978-981-15-3284-9_65 10.1016/j.ins.2007.05.030 10.1007/s11042-020-10255-3 10.1016/j.cma.2022.114616 10.3390/s22030855 10.1109/MDAT.2020.2976669 10.1098/rsta.2016.0191 10.1016/j.cma.2020.113609 10.1109/CEC.2013.6557555 10.1016/j.knosys.2022.110011 10.1007/s004250050096 10.1007/s12652-020-01704-w 10.1016/j.eswa.2013.07.067 10.1016/j.future.2019.02.028 10.1016/j.eswa.2021.116158 10.1007/s00521-020-04866-y 10.1504/IJBIC.2010.032124
ContentType	Journal Article
Copyright	The Author(s) 2023 The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml	– notice: The Author(s) 2023 – notice: The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID	C6C AAYXX CITATION 8FE 8FG ABJCF AFKRA ARAPS AZQEC BENPR BGLVJ CCPQU DWQXO GNUQQ HCIFZ JQ2 K7- L6V M7S P5Z P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PTHSS
DOI	10.1007/s11227-023-05513-8
DatabaseName	Springer Nature OA Free Journals CrossRef ProQuest SciTech Collection ProQuest Technology Collection Materials Science & Engineering Collection ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials - QC ProQuest Central ProQuest Technology Collection ProQuest One Community College ProQuest Central Korea ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database (ProQuest) ProQuest Engineering Collection Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Proquest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection
DatabaseTitle	CrossRef Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Engineering Collection ProQuest Central Korea ProQuest Central (New) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition Materials Science & Engineering Collection ProQuest One Academic ProQuest One Academic (New)
DatabaseTitleList	Computer Science Database CrossRef
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1573-0484
EndPage	799
ExternalDocumentID	10_1007_s11227_023_05513_8
GrantInformation_xml	– fundername: Karlsruher Institut für Technologie (KIT) (4220)
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C .4S .86 .DC .VR 06D 0R~ 0VY 123 199 1N0 1SB 2.D 203 28- 29L 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 4.4 406 408 409 40D 40E 5QI 5VS 67Z 6NX 78A 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYOK AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDBF ABDPE ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACUHS ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADMLS ADQRH ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHSBF AHYZX AI. AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN B-. B0M BA0 BBWZM BDATZ BGNMA BSONS C6C CAG COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 EAD EAP EAS EBD EBLON EBS EDO EIOEI EJD EMK EPL ESBYG ESX F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GXS H13 HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ H~9 I-F I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KOW LAK LLZTM M4Y MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P2P P9O PF0 PT4 PT5 QOK QOS R4E R89 R9I RHV RNI ROL RPX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TEORI TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW VH1 W23 W48 WH7 WK8 YLTOR Z45 Z7R Z7X Z7Z Z83 Z88 Z8M Z8N Z8R Z8T Z8W Z92 ZMTXR ~8M ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABJCF ABRTQ ACSTC ADHKG ADKFA AEZWR AFDZB AFFHD AFHIU AFKRA AFOHR AGQPQ AHPBZ AHWEU AIXLP ARAPS ATHPR AYFIA BENPR BGLVJ CCPQU CITATION HCIFZ K7- M7S PHGZM PHGZT PQGLB PTHSS 8FE 8FG AZQEC DWQXO GNUQQ JQ2 L6V P62 PKEHL PQEST PQQKQ PQUKI PRINS
ID	FETCH-LOGICAL-c363t-afad0b450cf67d1b072de7544dd321ed100af87e6b48c1eef8f0873d1d8fb8883
IEDL.DBID	M7S
ISICitedReferencesCount	52
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001021399300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0920-8542
IngestDate	Sun Nov 30 04:23:40 EST 2025 Sat Nov 29 04:27:45 EST 2025 Tue Nov 18 21:33:20 EST 2025 Fri Feb 21 02:40:36 EST 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Network clustering Internet of Things (IoT) Evolutionary algorithms Lotus effect Dragonfly algorithm Optimization
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c363t-afad0b450cf67d1b072de7544dd321ed100af87e6b48c1eef8f0873d1d8fb8883
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
OpenAccessLink	https://link.springer.com/10.1007/s11227-023-05513-8
PQID	3256589225
PQPubID	2043774
PageCount	39
ParticipantIDs	proquest_journals_3256589225 crossref_citationtrail_10_1007_s11227_023_05513_8 crossref_primary_10_1007_s11227_023_05513_8 springer_journals_10_1007_s11227_023_05513_8
PublicationCentury	2000
PublicationDate	20240100 2024-01-00 20240101
PublicationDateYYYYMMDD	2024-01-01
PublicationDate_xml	– month: 1 year: 2024 text: 20240100
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationSubtitle	An International Journal of High-Performance Computer Design, Analysis, and Use
PublicationTitle	The Journal of supercomputing
PublicationTitleAbbrev	J Supercomput
PublicationYear	2024
Publisher	Springer US Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer Nature B.V
References	Rajesh G, Mercilin Raajini X, Ashoka Rajan R, Gokuldhev M, Swetha C (2020) A multi-objective routing optimization using swarm intelligence in IoT networks. In: Intelligent Computing and Innovation on Data Science: Proceedings of ICTIDS 2019. Springer Singapore, pp 603–613 Nath S, Banik S, Seal A, Sarkar SK (2016) Optimizing MANET routing in AODV: an hybridization approach of ACO and firefly algorithm. In: 2016 Second International Conference on Research in Computational Intelligence and Communication networks (ICRCICN). IEEE, pp 122–127 AbualigahLAbd ElazizMSumariPGeemZWGandomiAHReptile search algorithm (RSA): a nature-inspired meta-heuristic optimizerExpert Syst Appl2022191116158 XueJShenBDung beetle optimizer: a new meta-heuristic algorithm for global optimizationJ Supercomput202379773057336 ArafatMYMohSA survey on cluster-based routing protocols for unmanned aerial vehicle networksIEEE Access20187498516 CollinsCMSafiuddinMLotus-leaf-inspired biomimetic coatings: different types, key properties, and applications in infrastructuresInfrastructures20227446 YangHLiZLiuZA method of routing optimization using CHNN in MANETJ Ambient Intell Humaniz Comput20191017591768 HeidariAAMirjaliliSFarisHAljarahIMafarjaMChenHHarris hawks optimization: algorithm and applicationsFuture Gener Comput Syst201997849872 KhaleelLRMitrasBAA novel hybrid Dragonfly algorithm with modified conjugate gradient methodInt J Comput Netw Commun Secur2020824048 ZhaoWWangLMirjaliliSArtificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applicationsComput Methods Appl Mech Eng20223881141944337753 ReynoldsAMRhodesCJThe Lévy flight paradigm: random search patterns and mechanismsEcology2009904877887 SivakumarPRadhikaMPerformance analysis of leach-ga over leach and leach-c in wsnProcedia Comput Sci2018125248256 ZamaniHNadimi-ShahrakiMHGandomiAHStarling murmuration optimizer: a novel bio-inspired algorithm for global and engineering optimizationComput Methods Appl Mech Eng20223921146164379773 Li J, Zhang Z, Xu J, Wong CP (2000) Self-cleaning materials—lotus effect surfaces. Kirk-Othmer Encyclopedia of Chemical Technology MohsinAHBakarKAZainalAOptimal control overhead based multi-metric routing for MANETWirel Netw20182423192335 Acı ÇI, Gülcan H (2019) A modified dragonfly optimization algorithm for single-and multiobjective problems using Brownian motion. Computational intelligence and neuroscience Husnain G, Anwar S, Shahzad F (2017).Performance evaluation of CLPSO and MOPSO routing algorithms for optimized clustering in vehicular Ad hoc networks. In: 2017 14th International Bhurban Conference on Applied Sciences and Technology (IBCAST). IEEE, pp 772–778 DebnathSBaishyaSSenDArifWA hybrid memory-based dragonfly algorithm with differential evolution for engineering applicationEng Comput20213727752802 ShiraniMRSafi-EsfahaniFBMDA: applying biogeography-based optimization algorithm and Mexican hat wavelet to improve dragonfly algorithmSoft Comput202024211597916004 Yang XS (2012) Flower pollination algorithm for global optimization. In: Unconventional Computation and Natural Computation: 11th International Conference, UCNC 2012, Orléan, France, September 3-7, 2012. Proceedings 11. Springer Berlin Heidelberg, pp 240–249 PanJSZhangLGWangRBSnášelVChuSCGannet optimization algorithm: a new metaheuristic algorithm for solving engineering optimization problemsMath Comput Simul20222023433734445169 CuevasECienfuegosMA new algorithm inspired in the behavior of the social-spider for constrained optimizationExpert Syst Appl2014412412425 GeorgeDTRajRERajkumarAMabelMCOptimal sizing of solar-wind based hybrid energy system using modified dragonfly algorithm for an institutionEnergy Convers Manage2023283116938 AroraVKSharmaVSachdevaMA survey on LEACH and other's routing protocols in wireless sensor networkOptik20161271665906600 Site: https://www.mathworks.com/matlabcentral/fileexchange/124810-benchmark-problems AkbariMAZareMAzizipanah-AbarghooeeRMirjaliliSDericheMThe cheetah optimizer: a nature-inspired metaheuristic algorithm for large-scale optimization problemsSci Rep202212110953 Dhumane A, Chiwhane S, Mangore Anirudh K, Ambala S (2022) Cluster-based energy-efficient routing in Internet of Things. In: ICT with Intelligent Applications: Proceedings of ICTIS 2022, Vol 1. Springer Nature Singapore, Singapore pp 415–427 WangNCHuangYFChenJCA stable weight-based on-demand routing protocol for mobile ad hoc networksInf Sci20071772455225537 Panda N, Pattanayak BK (2020) ACO-based secure routing protocols in MANETs. In: New Paradigm in Decision Science and Management: Proceedings of ICDSM 2018. Springer Singapore, pp 195–206 AbualigahLDiabatAMirjaliliSAbd ElazizMGandomiAHThe arithmetic optimization algorithmComput Methods Appl Mech Eng20213761136094199299 DehghaniMMontazeriZTrojovskáETrojovskýPCoati optimization algorithm: a new bio-inspired metaheuristic algorithm for solving optimization problemsKnowl-Based Syst2023259110011 NeinhuisCBarthlottWCharacterization and distribution of water-repellent, self-cleaning plant surfacesAnn Bot1997796667677 JiaHPengXLangCRemora optimization algorithmExpert Syst Appl2021185115665 KakueinejadMHHeydariAAskariMKeyniaFOptimal planning for the development of power system in respect to distributed generations based on the binary dragonfly algorithmAppl Sci202010144795 SinghPMittalNEfficient localisation approach for WSNs using hybrid DA–FA algorithmIET Commun2020141219751991 KarabogaDAkayBA comparative study of artificial bee colony algorithmAppl Math Comput200921411081322541051 AziziMAickelinUKhorshidiHABaghalzadeh ShishehgarkhanehMEnergy valley optimizer: a novel metaheuristic algorithm for global and engineering optimizationSci Rep2023131226 YuCCaiZYeXWangMZhaoXLiangGChenHLiCQuantum-like mutation-induced dragonfly-inspired optimization approachMath Comput Simul20201782592894118915 MirjaliliSLewisAThe whale optimization algorithmAdv Eng Softw2016955167 BarthlottWMailMNeinhuisCSuperhydrophobic hierarchically structured surfaces in biology: evolution, structural principles and biomimetic applicationsPhilos Trans R Soc A Math Phys Eng Sci2016374207320160191 Nivetha SK, Asokan R, Senthilkumaran N (2019) Metaheuristics in Mobile AdHoc network route optimization. In: 2019 TEQIP III Sponsored International Conference on Microwave Integrated Circuits, Photonics and Wireless Networks (IMICPW). IEEE, pp 414–418 LeTHuWCorkePJhaSERTP: energy-efficient and reliable transport protocol for data streaming in wireless sensor networksComput Commun2009327–1011541171 SinghHSawleYDixitSMalikHMárquezFPGOptimization of reactive power using dragonfly algorithm in DG integrated distribution systemElectr Power Syst Res2023220109351 Yousaf A, Ahmad F, Hamid S, Khan F (2019) Performance comparison of various LEACH protocols in wireless sensor networks. In: 2019 IEEE 15th International Colloquium on Signal Processing & its Applications (CSPA). IEEE, pp 108–113 YangXSFirefly algorithm, stochastic test functions and design optimisationInt J Bio-inspir Comput2010227884 Rathi PS, Mallikarjuna Rao CH (2020) Survey paper on routing in MANETs for optimal route selection based on routing protocol with particle swarm optimization and different ant colony optimization protocol. In: Smart Intelligent Computing and Applications: Proceedings of the Third International Conference on Smart Computing and Informatics, Vol 1. Springer Singapore, pp 539–547 Khapre SP, Chopra S, Khan A, Sharma P, Shankar A (2020) Optimized routing method for wireless sensor networks based on improved ant colony algorithm. In: 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, pp 455–458 ArumugamMSRaoMVCTanAWA novel and effective particle swarm optimization like algorithm with extrapolation techniqueAppl Soft Comput200991308320 Al-TurjmanFMostardaLEverEDarwishAKhalilNSNetwork experience scheduling and routing approach for big data transmission in the Internet of ThingsIeee Access201971450114512 MeraihiYRamdane-CherifAAcheliDMahseurMDragonfly algorithm: a comprehensive review and applicationsNeural Comput Appl2020321662516646 AziziMTalatahariSGandomiAHFire Hawk optimizer: a novel metaheuristic algorithmArtif Intell Rev2023561287363 JoshiMKalitaKJangirPAhmadianfarIChakrabortySA conceptual comparison of Dragonfly algorithm variants for CEC-2021 global optimization problemsArab J Sci Eng202348215631593 HashimFAHussainKHousseinEHMabroukMSAl-AtabanyWArchimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problemsAppl Intell20215115311551 KumarNVidyarthiDPA green routing algorithm for IoT-enabled software defined wireless sensor networkIEEE Sens J2018182294499460 BarthlottWNeinhuisCPurity of the sacred lotus, or escape from contamination in biological surfacesPlanta199720218 AbdollahzadehBGharehchopoghFSMirjaliliSAfrican vultures optimization algorithm: a new nature-inspired metaheuristic algorithm for global optimization problemsComput Ind Eng2021158107408 Mahfoud SW (1995) A comparison of parallel and sequential niching methods. In: Conference on Genetic Algorithms, Vol 136, p 143 TrojovskýPDehghaniMPelican optimization algorithm: a novel nature-inspired algorithm for engineering applicationsSensors2022223855 Kumar S, Sinha DK, Kumar V (2020) An approach to improve lifetime of MANET via power aware routing protocol and genetic algorithm. In: 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). IEEE, pp 550–553 AlshinwanMAbualigahLShehabMElazizMAKhasawnehAMAlaboolHHamadHADragonfly algorithm: a comprehensive survey of its results, variants, and applicationsMultimed Tools Appl2021801497915016 Tanabe R, Fukunaga A (2013) Success-history based parameter adaptation for differential evolution. In: 2013 IEEE Congress on Evolutionary Computation. IEEE, pp 71–78 BatthKKSinghRSwarm intelligence for routing in mobile Ad Hoc networksInt J Adv Inf Sci Technol (IJAIST)201610.1109/SIS.2005.1501605 PasrichaSAyoubRKishinevskyMMandalSKOgrasU M Joshi (5513_CR28) 2023; 48 P Singh (5513_CR66) 2020; 14 AA Heidari (5513_CR2) 2019; 97 LR Khaleel (5513_CR23) 2020; 8 H Zamani (5513_CR6) 2022; 392 H Singh (5513_CR27) 2023; 220 5513_CR56 5513_CR57 5513_CR58 5513_CR52 H Jia (5513_CR12) 2021; 185 AM Reynolds (5513_CR21) 2009; 90 P Sivakumar (5513_CR4) 2018; 125 MA Akbari (5513_CR5) 2022; 12 NC Wang (5513_CR34) 2007; 177 DT George (5513_CR26) 2023; 283 AH Mohsin (5513_CR32) 2018; 24 Y Meraihi (5513_CR49) 2020; 32 5513_CR48 M Alshinwan (5513_CR18) 2021; 80 5513_CR44 5513_CR40 5513_CR41 M Azizi (5513_CR14) 2023; 56 MH Kakueinejad (5513_CR24) 2020; 10 5513_CR43 L Abualigah (5513_CR10) 2022; 191 W Zhao (5513_CR8) 2022; 388 VK Arora (5513_CR47) 2016; 127 J Xue (5513_CR16) 2023; 79 S Mirjalili (5513_CR13) 2016; 95 XS Yang (5513_CR61) 2010; 2 N Kumar (5513_CR45) 2018; 18 D Karaboga (5513_CR60) 2009; 214 5513_CR1 M Yamamoto (5513_CR53) 2015; 31 B Abdollahzadeh (5513_CR9) 2021; 158 5513_CR37 FA Hashim (5513_CR64) 2021; 51 H Yang (5513_CR33) 2019; 10 5513_CR39 W Barthlott (5513_CR50) 1997; 202 C Neinhuis (5513_CR51) 1997; 79 E Cuevas (5513_CR59) 2014; 41 C Yu (5513_CR22) 2020; 178 5513_CR35 5513_CR36 T Le (5513_CR38) 2009; 32 M Dehghani (5513_CR11) 2023; 259 Y Zhang (5513_CR3) 2020; 11 KK Batth (5513_CR42) 2016 JS Pan (5513_CR65) 2022; 202 M Azizi (5513_CR15) 2023; 13 MY Arafat (5513_CR30) 2018; 7 F Al-Turjman (5513_CR31) 2019; 7 P Trojovský (5513_CR7) 2022; 22 MR Shirani (5513_CR19) 2020; 24 M Shah (5513_CR25) 2023; 23 5513_CR29 CM Collins (5513_CR55) 2022; 7 5513_CR20 MS Arumugam (5513_CR62) 2009; 9 S Pasricha (5513_CR46) 2020; 37 W Barthlott (5513_CR54) 2016; 374 L Abualigah (5513_CR63) 2021; 376 S Debnath (5513_CR17) 2021; 37
References_xml	– reference: AlshinwanMAbualigahLShehabMElazizMAKhasawnehAMAlaboolHHamadHADragonfly algorithm: a comprehensive survey of its results, variants, and applicationsMultimed Tools Appl2021801497915016 – reference: GeorgeDTRajRERajkumarAMabelMCOptimal sizing of solar-wind based hybrid energy system using modified dragonfly algorithm for an institutionEnergy Convers Manage2023283116938 – reference: SinghPMittalNEfficient localisation approach for WSNs using hybrid DA–FA algorithmIET Commun2020141219751991 – reference: AbualigahLAbd ElazizMSumariPGeemZWGandomiAHReptile search algorithm (RSA): a nature-inspired meta-heuristic optimizerExpert Syst Appl2022191116158 – reference: MeraihiYRamdane-CherifAAcheliDMahseurMDragonfly algorithm: a comprehensive review and applicationsNeural Comput Appl2020321662516646 – reference: ‏Site: https://www.mathworks.com/matlabcentral/fileexchange/124810-benchmark-problems – reference: AziziMAickelinUKhorshidiHABaghalzadeh ShishehgarkhanehMEnergy valley optimizer: a novel metaheuristic algorithm for global and engineering optimizationSci Rep2023131226 – reference: ArumugamMSRaoMVCTanAWA novel and effective particle swarm optimization like algorithm with extrapolation techniqueAppl Soft Comput200991308320 – reference: KumarNVidyarthiDPA green routing algorithm for IoT-enabled software defined wireless sensor networkIEEE Sens J2018182294499460 – reference: ReynoldsAMRhodesCJThe Lévy flight paradigm: random search patterns and mechanismsEcology2009904877887 – reference: PasrichaSAyoubRKishinevskyMMandalSKOgrasUYA survey on energy management for mobile and IoT devicesIEEE Des Test2020375724 – reference: Li J, Zhang Z, Xu J, Wong CP (2000) Self-cleaning materials—lotus effect surfaces. Kirk-Othmer Encyclopedia of Chemical Technology – reference: Dhumane A, Chiwhane S, Mangore Anirudh K, Ambala S (2022) Cluster-based energy-efficient routing in Internet of Things. In: ICT with Intelligent Applications: Proceedings of ICTIS 2022, Vol 1. Springer Nature Singapore, Singapore pp 415–427 – reference: HashimFAHussainKHousseinEHMabroukMSAl-AtabanyWArchimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problemsAppl Intell20215115311551 – reference: PanJSZhangLGWangRBSnášelVChuSCGannet optimization algorithm: a new metaheuristic algorithm for solving engineering optimization problemsMath Comput Simul20222023433734445169 – reference: XueJShenBDung beetle optimizer: a new meta-heuristic algorithm for global optimizationJ Supercomput202379773057336 – reference: BarthlottWMailMNeinhuisCSuperhydrophobic hierarchically structured surfaces in biology: evolution, structural principles and biomimetic applicationsPhilos Trans R Soc A Math Phys Eng Sci2016374207320160191 – reference: ShiraniMRSafi-EsfahaniFBMDA: applying biogeography-based optimization algorithm and Mexican hat wavelet to improve dragonfly algorithmSoft Comput202024211597916004 – reference: Husnain G, Anwar S, Shahzad F (2017).Performance evaluation of CLPSO and MOPSO routing algorithms for optimized clustering in vehicular Ad hoc networks. In: 2017 14th International Bhurban Conference on Applied Sciences and Technology (IBCAST). IEEE, pp 772–778 – reference: YangXSFirefly algorithm, stochastic test functions and design optimisationInt J Bio-inspir Comput2010227884 – reference: Rathi PS, Mallikarjuna Rao CH (2020) Survey paper on routing in MANETs for optimal route selection based on routing protocol with particle swarm optimization and different ant colony optimization protocol. In: Smart Intelligent Computing and Applications: Proceedings of the Third International Conference on Smart Computing and Informatics, Vol 1. Springer Singapore, pp 539–547 – reference: Al-TurjmanFMostardaLEverEDarwishAKhalilNSNetwork experience scheduling and routing approach for big data transmission in the Internet of ThingsIeee Access201971450114512 – reference: Rajesh G, Mercilin Raajini X, Ashoka Rajan R, Gokuldhev M, Swetha C (2020) A multi-objective routing optimization using swarm intelligence in IoT networks. In: Intelligent Computing and Innovation on Data Science: Proceedings of ICTIDS 2019. Springer Singapore, pp 603–613 – reference: AroraVKSharmaVSachdevaMA survey on LEACH and other's routing protocols in wireless sensor networkOptik20161271665906600 – reference: Mahfoud SW (1995) A comparison of parallel and sequential niching methods. In: Conference on Genetic Algorithms, Vol 136, p 143) – reference: Nivetha SK, Asokan R, Senthilkumaran N (2019) Metaheuristics in Mobile AdHoc network route optimization. In: 2019 TEQIP III Sponsored International Conference on Microwave Integrated Circuits, Photonics and Wireless Networks (IMICPW). IEEE, pp 414–418 – reference: NeinhuisCBarthlottWCharacterization and distribution of water-repellent, self-cleaning plant surfacesAnn Bot1997796667677 – reference: KarabogaDAkayBA comparative study of artificial bee colony algorithmAppl Math Comput200921411081322541051 – reference: KhaleelLRMitrasBAA novel hybrid Dragonfly algorithm with modified conjugate gradient methodInt J Comput Netw Commun Secur2020824048 – reference: MirjaliliSLewisAThe whale optimization algorithmAdv Eng Softw2016955167 – reference: AziziMTalatahariSGandomiAHFire Hawk optimizer: a novel metaheuristic algorithmArtif Intell Rev2023561287363 – reference: AbualigahLDiabatAMirjaliliSAbd ElazizMGandomiAHThe arithmetic optimization algorithmComput Methods Appl Mech Eng20213761136094199299 – reference: JiaHPengXLangCRemora optimization algorithmExpert Syst Appl2021185115665 – reference: YuCCaiZYeXWangMZhaoXLiangGChenHLiCQuantum-like mutation-induced dragonfly-inspired optimization approachMath Comput Simul20201782592894118915 – reference: ZhaoWWangLMirjaliliSArtificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applicationsComput Methods Appl Mech Eng20223881141944337753 – reference: BarthlottWNeinhuisCPurity of the sacred lotus, or escape from contamination in biological surfacesPlanta199720218 – reference: KakueinejadMHHeydariAAskariMKeyniaFOptimal planning for the development of power system in respect to distributed generations based on the binary dragonfly algorithmAppl Sci202010144795 – reference: TrojovskýPDehghaniMPelican optimization algorithm: a novel nature-inspired algorithm for engineering applicationsSensors2022223855 – reference: WangNCHuangYFChenJCA stable weight-based on-demand routing protocol for mobile ad hoc networksInf Sci20071772455225537 – reference: ZamaniHNadimi-ShahrakiMHGandomiAHStarling murmuration optimizer: a novel bio-inspired algorithm for global and engineering optimizationComput Methods Appl Mech Eng20223921146164379773 – reference: JoshiMKalitaKJangirPAhmadianfarIChakrabortySA conceptual comparison of Dragonfly algorithm variants for CEC-2021 global optimization problemsArab J Sci Eng202348215631593 – reference: DebnathSBaishyaSSenDArifWA hybrid memory-based dragonfly algorithm with differential evolution for engineering applicationEng Comput20213727752802 – reference: Tanabe R, Fukunaga A (2013) Success-history based parameter adaptation for differential evolution. In: 2013 IEEE Congress on Evolutionary Computation. IEEE, pp 71–78 – reference: Acı ÇI, Gülcan H (2019) A modified dragonfly optimization algorithm for single-and multiobjective problems using Brownian motion. Computational intelligence and neuroscience – reference: AkbariMAZareMAzizipanah-AbarghooeeRMirjaliliSDericheMThe cheetah optimizer: a nature-inspired metaheuristic algorithm for large-scale optimization problemsSci Rep202212110953 – reference: YamamotoMNishikawaNMayamaHNonomuraYYokojimaSNakamuraSUchidaKTheoretical explanation of the lotus effect: superhydrophobic property changes by removal of nanostructures from the surface of a lotus leafLangmuir2015312673557363 – reference: AbdollahzadehBGharehchopoghFSMirjaliliSAfrican vultures optimization algorithm: a new nature-inspired metaheuristic algorithm for global optimization problemsComput Ind Eng2021158107408 – reference: Kumar S, Sinha DK, Kumar V (2020) An approach to improve lifetime of MANET via power aware routing protocol and genetic algorithm. In: 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). IEEE, pp 550–553 – reference: Yousaf A, Ahmad F, Hamid S, Khan F (2019) Performance comparison of various LEACH protocols in wireless sensor networks. In: 2019 IEEE 15th International Colloquium on Signal Processing & its Applications (CSPA). IEEE, pp 108–113 – reference: CollinsCMSafiuddinMLotus-leaf-inspired biomimetic coatings: different types, key properties, and applications in infrastructuresInfrastructures20227446 – reference: SinghHSawleYDixitSMalikHMárquezFPGOptimization of reactive power using dragonfly algorithm in DG integrated distribution systemElectr Power Syst Res2023220109351 – reference: YangHLiZLiuZA method of routing optimization using CHNN in MANETJ Ambient Intell Humaniz Comput20191017591768 – reference: Panda N, Pattanayak BK (2020) ACO-based secure routing protocols in MANETs. In: New Paradigm in Decision Science and Management: Proceedings of ICDSM 2018. Springer Singapore, pp 195–206 – reference: CuevasECienfuegosMA new algorithm inspired in the behavior of the social-spider for constrained optimizationExpert Syst Appl2014412412425 – reference: ArafatMYMohSA survey on cluster-based routing protocols for unmanned aerial vehicle networksIEEE Access20187498516 – reference: HeidariAAMirjaliliSFarisHAljarahIMafarjaMChenHHarris hawks optimization: algorithm and applicationsFuture Gener Comput Syst201997849872 – reference: MohsinAHBakarKAZainalAOptimal control overhead based multi-metric routing for MANETWirel Netw20182423192335 – reference: Khapre SP, Chopra S, Khan A, Sharma P, Shankar A (2020) Optimized routing method for wireless sensor networks based on improved ant colony algorithm. In: 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, pp 455–458 – reference: ZhangYWangYA novel energy-aware bio-inspired clustering scheme for IoT communicationJ Ambient Intell Humaniz Comput20201142394248 – reference: ShahMBoradeHSanghaviVPurohitAWankhedeVVakhariaVEnhancing tool wear prediction accuracy using walsh-hadamard transform, DCGAN and Dragonfly algorithm-based feature selectionSensors20232383833 – reference: Yang XS (2012) Flower pollination algorithm for global optimization. In: Unconventional Computation and Natural Computation: 11th International Conference, UCNC 2012, Orléan, France, September 3-7, 2012. Proceedings 11. Springer Berlin Heidelberg, pp 240–249 – reference: LeTHuWCorkePJhaSERTP: energy-efficient and reliable transport protocol for data streaming in wireless sensor networksComput Commun2009327–1011541171 – reference: DehghaniMMontazeriZTrojovskáETrojovskýPCoati optimization algorithm: a new bio-inspired metaheuristic algorithm for solving optimization problemsKnowl-Based Syst2023259110011 – reference: SivakumarPRadhikaMPerformance analysis of leach-ga over leach and leach-c in wsnProcedia Comput Sci2018125248256 – reference: BatthKKSinghRSwarm intelligence for routing in mobile Ad Hoc networksInt J Adv Inf Sci Technol (IJAIST)201610.1109/SIS.2005.1501605 – reference: Nath S, Banik S, Seal A, Sarkar SK (2016) Optimizing MANET routing in AODV: an hybridization approach of ACO and firefly algorithm. In: 2016 Second International Conference on Research in Computational Intelligence and Communication networks (ICRCICN). IEEE, pp 122–127 – volume: 24 start-page: 15979 issue: 21 year: 2020 ident: 5513_CR19 publication-title: Soft Comput doi: 10.1007/s00500-020-05340-6 – volume: 32 start-page: 1154 issue: 7–10 year: 2009 ident: 5513_CR38 publication-title: Comput Commun doi: 10.1016/j.comcom.2008.12.045 – ident: 5513_CR56 doi: 10.1007/978-3-642-32894-7_27 – volume: 283 start-page: 116938 year: 2023 ident: 5513_CR26 publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2023.116938 – ident: 5513_CR35 doi: 10.1109/ICIMIA48430.2020.9074912 – volume: 158 start-page: 107408 year: 2021 ident: 5513_CR9 publication-title: Comput Ind Eng doi: 10.1016/j.cie.2021.107408 – volume: 23 start-page: 3833 issue: 8 year: 2023 ident: 5513_CR25 publication-title: Sensors doi: 10.3390/s23083833 – volume: 9 start-page: 308 issue: 1 year: 2009 ident: 5513_CR62 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2008.04.016 – volume: 7 start-page: 14501 year: 2019 ident: 5513_CR31 publication-title: Ieee Access doi: 10.1109/ACCESS.2019.2893501 – volume: 37 start-page: 2775 year: 2021 ident: 5513_CR17 publication-title: Eng Comput doi: 10.1007/s00366-020-00958-4 – volume: 12 start-page: 10953 issue: 1 year: 2022 ident: 5513_CR5 publication-title: Sci Rep doi: 10.1038/s41598-022-14338-z – volume: 95 start-page: 51 year: 2016 ident: 5513_CR13 publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2016.01.008 – volume: 185 start-page: 115665 year: 2021 ident: 5513_CR12 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2021.115665 – volume: 90 start-page: 877 issue: 4 year: 2009 ident: 5513_CR21 publication-title: Ecology doi: 10.1890/08-0153.1 – volume: 214 start-page: 108 issue: 1 year: 2009 ident: 5513_CR60 publication-title: Appl Math Comput – ident: 5513_CR29 doi: 10.1007/978-981-19-3571-8_40 – ident: 5513_CR44 doi: 10.1109/ICRCICN.2016.7813643 – volume: 31 start-page: 7355 issue: 26 year: 2015 ident: 5513_CR53 publication-title: Langmuir doi: 10.1021/acs.langmuir.5b00670 – volume: 125 start-page: 248 year: 2018 ident: 5513_CR4 publication-title: Procedia Comput Sci doi: 10.1016/j.procs.2017.12.034 – volume: 178 start-page: 259 year: 2020 ident: 5513_CR22 publication-title: Math Comput Simul doi: 10.1016/j.matcom.2020.06.012 – year: 2016 ident: 5513_CR42 publication-title: Int J Adv Inf Sci Technol (IJAIST) doi: 10.1109/SIS.2005.1501605 – volume: 14 start-page: 1975 issue: 12 year: 2020 ident: 5513_CR66 publication-title: IET Commun doi: 10.1049/iet-com.2019.1311 – ident: 5513_CR36 doi: 10.1109/IMICPW.2019.8933284 – volume: 8 start-page: 40 issue: 2 year: 2020 ident: 5513_CR23 publication-title: Int J Comput Netw Commun Secur doi: 10.47277/IJCNCS/8(2)2 – volume: 7 start-page: 498 year: 2018 ident: 5513_CR30 publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2885539 – volume: 79 start-page: 7305 issue: 7 year: 2023 ident: 5513_CR16 publication-title: J Supercomput doi: 10.1007/s11227-022-04959-6 – ident: 5513_CR52 – ident: 5513_CR43 doi: 10.1007/978-981-13-9282-5_51 – ident: 5513_CR48 doi: 10.1109/CSPA.2019.8695973 – volume: 388 start-page: 114194 year: 2022 ident: 5513_CR8 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2021.114194 – volume: 48 start-page: 1563 issue: 2 year: 2023 ident: 5513_CR28 publication-title: Arab J Sci Eng doi: 10.1007/s13369-022-06880-9 – volume: 24 start-page: 2319 year: 2018 ident: 5513_CR32 publication-title: Wirel Netw doi: 10.1007/s11276-017-1468-3 – ident: 5513_CR41 doi: 10.1109/IBCAST.2017.7868141 – volume: 127 start-page: 6590 issue: 16 year: 2016 ident: 5513_CR47 publication-title: Optik doi: 10.1016/j.ijleo.2016.04.041 – volume: 51 start-page: 1531 year: 2021 ident: 5513_CR64 publication-title: Appl Intell doi: 10.1007/s10489-020-01893-z – ident: 5513_CR1 – volume: 7 start-page: 46 issue: 4 year: 2022 ident: 5513_CR55 publication-title: Infrastructures doi: 10.3390/infrastructures7040046 – volume: 18 start-page: 9449 issue: 22 year: 2018 ident: 5513_CR45 publication-title: IEEE Sens J doi: 10.1109/JSEN.2018.2869629 – volume: 79 start-page: 667 issue: 6 year: 1997 ident: 5513_CR51 publication-title: Ann Bot doi: 10.1006/anbo.1997.0400 – volume: 220 start-page: 109351 year: 2023 ident: 5513_CR27 publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2023.109351 – ident: 5513_CR37 doi: 10.1007/978-981-13-9330-3_18 – volume: 10 start-page: 1759 year: 2019 ident: 5513_CR33 publication-title: J Ambient Intell Humaniz Comput doi: 10.1007/s12652-017-0614-1 – volume: 10 start-page: 4795 issue: 14 year: 2020 ident: 5513_CR24 publication-title: Appl Sci doi: 10.3390/app10144795 – volume: 202 start-page: 343 year: 2022 ident: 5513_CR65 publication-title: Math Comput Simul doi: 10.1016/j.matcom.2022.06.007 – ident: 5513_CR40 doi: 10.1109/Confluence47617.2020.9058312 – volume: 56 start-page: 287 issue: 1 year: 2023 ident: 5513_CR14 publication-title: Artif Intell Rev doi: 10.1007/s10462-022-10173-w – volume: 13 start-page: 226 issue: 1 year: 2023 ident: 5513_CR15 publication-title: Sci Rep doi: 10.1038/s41598-022-27344-y – ident: 5513_CR20 doi: 10.1155/2019/6871298 – ident: 5513_CR39 doi: 10.1007/978-981-15-3284-9_65 – volume: 177 start-page: 5522 issue: 24 year: 2007 ident: 5513_CR34 publication-title: Inf Sci doi: 10.1016/j.ins.2007.05.030 – volume: 80 start-page: 14979 year: 2021 ident: 5513_CR18 publication-title: Multimed Tools Appl doi: 10.1007/s11042-020-10255-3 – volume: 392 start-page: 114616 year: 2022 ident: 5513_CR6 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2022.114616 – volume: 22 start-page: 855 issue: 3 year: 2022 ident: 5513_CR7 publication-title: Sensors doi: 10.3390/s22030855 – volume: 37 start-page: 7 issue: 5 year: 2020 ident: 5513_CR46 publication-title: IEEE Des Test doi: 10.1109/MDAT.2020.2976669 – volume: 374 start-page: 20160191 issue: 2073 year: 2016 ident: 5513_CR54 publication-title: Philos Trans R Soc A Math Phys Eng Sci doi: 10.1098/rsta.2016.0191 – volume: 376 start-page: 113609 year: 2021 ident: 5513_CR63 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2020.113609 – ident: 5513_CR57 doi: 10.1109/CEC.2013.6557555 – volume: 259 start-page: 110011 year: 2023 ident: 5513_CR11 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2022.110011 – volume: 202 start-page: 1 year: 1997 ident: 5513_CR50 publication-title: Planta doi: 10.1007/s004250050096 – volume: 11 start-page: 4239 year: 2020 ident: 5513_CR3 publication-title: J Ambient Intell Humaniz Comput doi: 10.1007/s12652-020-01704-w – volume: 41 start-page: 412 issue: 2 year: 2014 ident: 5513_CR59 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2013.07.067 – volume: 97 start-page: 849 year: 2019 ident: 5513_CR2 publication-title: Future Gener Comput Syst doi: 10.1016/j.future.2019.02.028 – volume: 191 start-page: 116158 year: 2022 ident: 5513_CR10 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2021.116158 – volume: 32 start-page: 16625 year: 2020 ident: 5513_CR49 publication-title: Neural Comput Appl doi: 10.1007/s00521-020-04866-y – ident: 5513_CR58 – volume: 2 start-page: 78 issue: 2 year: 2010 ident: 5513_CR61 publication-title: Int J Bio-inspir Comput doi: 10.1504/IJBIC.2010.032124
SSID	ssj0004373
Score	2.5320632
Snippet	Here we introduce a new evolutionary algorithm called the Lotus Effect Algorithm, which combines efficient operators from the dragonfly algorithm, such as the...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	761
SubjectTerms	Accuracy Benchmarks Biogeography Clustering Compilers Computer Science Data transmission Design engineering Design optimization Energy consumption Energy efficiency Evolutionary algorithms Flowers Heuristic Internet of Things Interpreters Optimization algorithms Optimization techniques Performance evaluation Processor Architectures Productivity Programming Languages Sensors Wireless networks
SummonAdditionalLinks	– databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8NAEF60evBifWK1yh48KLqQ3Tx2461Ii4dSxEfpLST70EKblib19zt5GSsq6DmTYTP7mG8yO98gdE6Z50thFAE0zojDI48IwBEEnLPxvAhCn5xLb9jng4EYjfz7sigsqW67VynJ_KSui90oY5yAjyFW1pWEiHW0Ae5OZA0bHh6HdTWkXeSVfQiMhOuwslTmex2r7qjGmF_Sorm36TX_N84dtF2iS9wplsMuWtPxHmpWnRtwuZH30bw_S5cJLi5z4BkcG9OyHhOHk5fZYpy-TvFFv9u5vMEhnuTCBQUoGcdZbl6rT4KAe7GueQ2xym-FrKg9QM-97tPtHSl7LxBpe3ZKQhMqK3JcSxqPKxpZnCmdkeUpZTOqFXxqaATXXuQISbU2wliC24oqYSKIqu1D1IhnsT5CmAtfSmbzyPiWY7SXMdBBlAjgjobcWE4L0WoKAlkSk2f9MSZBTamcmTQAkwa5SQPRQlcf78wLWo5fpdvVzAblFk0CG8CeC-uSuS10Xc1k_fhnbcd_Ez9BWwyAUPHbpo0a6WKpT9GmfEvHyeIsX7rvePnnPg priority: 102 providerName: Springer Nature
Title	Lotus effect optimization algorithm (LEA): a lotus nature-inspired algorithm for engineering design optimization
URI	https://link.springer.com/article/10.1007/s11227-023-05513-8 https://www.proquest.com/docview/3256589225
Volume	80
WOSCitedRecordID	wos001021399300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1573-0484 dateEnd: 20241212 omitProxy: false ssIdentifier: ssj0004373 issn: 0920-8542 databaseCode: P5Z dateStart: 20230101 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database (ProQuest) customDbUrl: eissn: 1573-0484 dateEnd: 20241212 omitProxy: false ssIdentifier: ssj0004373 issn: 0920-8542 databaseCode: K7- dateStart: 20230101 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: Engineering Database customDbUrl: eissn: 1573-0484 dateEnd: 20241212 omitProxy: false ssIdentifier: ssj0004373 issn: 0920-8542 databaseCode: M7S dateStart: 20230101 isFulltext: true titleUrlDefault: http://search.proquest.com providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1573-0484 dateEnd: 20241212 omitProxy: false ssIdentifier: ssj0004373 issn: 0920-8542 databaseCode: BENPR dateStart: 20230101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1573-0484 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004373 issn: 0920-8542 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT9wwEB7xOnDpFgrqAl35wIGqWMTOww4XRKtFSKxWKygIcYkSPyjSsrtls_39HScOKZXgwsWXOKMon-2Z8cx8A7DPeJIqaTVFa5zTSBQJlWhHUFTONkkKdH0qLr2bgRgO5e1tOvIXbnOfVtmcidVBrafK3ZEfhaibYxTD45PZb-q6Rrnoqm-hsQyrjiWBVal7V21dZFhHmFN0kWQccV80U5fOMc4FRY1FA9fjhMqXiqm1Nv8LkFZ656zz3i_-CB-8xUlO6yWyAUtmsgmdppsD8Zv7E8wG03IxJ3WCB5niUfLoazRJPr5HweWvR3Iw6J9-PSY5GVeTa1pQ-jBx8Xqj_5mItjAxLdch0VWmyAuxW3B91v_545z6fgxUhUlY0tzmOiiiOFA2EZoVgeDaOAI9rUPOjMYfm1spTFJEUjFjrLSBFKFmWtoCPe1wG1Ym04n5DETIVCkeisKmQWRN4ljp0HNEg4_lwgZRF1gDRqY8WbnrmTHOWpplB2CGAGYVgJnswrfnd2Y1Vcebs_ca1DK_bedZC1kXDhvc28evS9t5W9ourHM0huqrmz1YKZ8W5gusqT_lw_ypB6vf-8PRZQ-WLwTtVUsYx1F8h-Pl1c1f-1716Q
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LTxRBEK4gmuhFVCSuoPRBE4x27MfsdA8JMUQhEIYNBzDcxpl-AMmyu7ADxj_Fb6R6Hg6YwI2D15meSnr663p0dX0F8IGLODHaW4reuKCRKmKq0Y-gaJx9HBcY-lRcej9TNRjow8Nkbwau2lqYcK2y1YmVorZjE87Iv0q0zX0UI_rfJmc0dI0K2dW2hUYNix335zeGbNO17R-4vh-F2NzY_75Fm64C1MhYljT3uWVF1GfGx8rygilhXaCBs1YK7ixnLPdaubiItOHOee2ZVtJyq32B8aJEuY_gcSTxYUgCK9rVYco6o51gSKb7kWiKdOpSPS6EomghKQs9Vai-bQg77_afhGxl5zbn_rc_9AKeNx41Wa-3wEuYcaNXMNd2qyCN8pqHSTouL6akvsBCxqgqT5saVJIPj3Ai5fEpWUk31j-tkpwMq8E17Sk9GYX7CM7eGIi-PnEdlyOx1U2YW2Jfw8GDzHsBZkfjkXsDROnEGCFV4RMWeRcH1j2MjNGh5bnyLOoBbxc_Mw0Ze-gJMsw6GukAmAwBk1WAyXQPPv_9ZlJTkdw7eqlFSdaopWnWQaQHX1qcda_vlvb2fmnL8HRrfzfN0u3BziI8E-j41cdUSzBbnl-4d_DEXJYn0_P31YYh8Ouh8XcNmodQDQ
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dT8IwEL8oGuOL-BlR1D74oNGGrRtr5xtRiEZCSFTC27KtrZLAIDD8-2334cCoifF5t8t2bXe_2939DuDcJI4bMsmxQuME2zRwMFM4AivnLB0nUKFPwqXXa9NOh_X7bnehiz-pds9TkmlPg2ZpiuLahMta0fhmEkKx8jfY0BNKMFuFNVsX0ut4_alXdEZaaY7ZVUESq9ska5v5Xseyayrw5pcUaeJ5WuX_P_M2bGWoEzXSbbIDKyLahXI-0QFlB3wPJu1xPJ-htMgDjdXnZJT1aSJ_-DqeDuK3EbpoNxuXN8hHw0Q4pQbFg0jn7AVfEFR4GImC7xDxpFpkSe0-vLSaz7f3OJvJgEPLsWLsS58bgV03QulQbgYGJVxoEj3OLWIKrl7Vl4wKJ7BZaAohmTQYtbjJmQxUtG0dQCkaR-IQEGVuGBKLBtI1bCkczUynokcF-kyfSsOugJkvhxdmhOV6bsbQK6iWtUk9ZVIvManHKnD1ec8kpev4Vbqar7KXHd2ZZykQWFf7ldQrcJ2vanH5Z21HfxM_g43uXctrP3Qej2GTKKyU_tmpQimezsUJrIfv8WA2PU129AfG5_MG
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Lotus+effect+optimization+algorithm+%28LEA%29%3A+a+lotus+nature-inspired+algorithm+for+engineering+design+optimization&rft.jtitle=The+Journal+of+supercomputing&rft.au=Dalirinia%2C+Elham&rft.au=Jalali%2C+Mehrdad&rft.au=Yaghoobi%2C+Mahdi&rft.au=Tabatabaee%2C+Hamid&rft.date=2024-01-01&rft.pub=Springer+Nature+B.V&rft.issn=0920-8542&rft.eissn=1573-0484&rft.volume=80&rft.issue=1&rft.spage=761&rft.epage=799&rft_id=info:doi/10.1007%2Fs11227-023-05513-8
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0920-8542&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0920-8542&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0920-8542&client=summon