Table Of ContentStudies in Computational Intelligence 1054
Anupam Biswas
Can B. Kalayci
Seyedali Mirjalili Editors
Advances
in Swarm
Intelligence
Variations and Adaptations
for Optimization Problems
Studies in Computational Intelligence
Volume 1054
SeriesEditor
JanuszKacprzyk,PolishAcademyofSciences,Warsaw,Poland
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· ·
Anupam Biswas Can B. Kalayci
Seyedali Mirjalili
Editors
Advances in Swarm
Intelligence
Variations and Adaptations for Optimization
Problems
Editors
AnupamBiswas CanB.Kalayci
DepartmentofComputerScience DepartmentofIndustrialEngineering
andEngineering PamukkaleUniversity
NationalInstituteOfTechnologySilchar Pamukkale,Turkey
Cachar,Assam,India
SeyedaliMirjalili
CentreforArtificialIntelligenceResearch
andOptimisation
TorrensUniversityAustralia
Brisbane,QLD,Australia
UniversityResearchandInnovationCenter
ObudaUniversity
Budapest,Hungary
ISSN 1860-949X ISSN 1860-9503 (electronic)
StudiesinComputationalIntelligence
ISBN 978-3-031-09834-5 ISBN 978-3-031-09835-2 (eBook)
https://doi.org/10.1007/978-3-031-09835-2
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Preface
SwarmIntelligence(SI)hasgrownsignificantly,bothfromtheperspectiveofalgo-
rithmicdevelopmentandapplicationscoveringalmostalldisciplinesinbothscience
andtechnology.Generallyspeaking,thealgorithmsthatcomeunderSIdomainare
typically population-based meta-heuristics techniques and are mostly inspired by
nature. This book strives to cover all the major SI techniques, including particle
swarmoptimization,antcolonyoptimization,fireflyalgorithm,dragonflyalgorithm,
cuckoosearch,andmanymore.DifferentvariantsofsuchSItechniqueshavebeen
developed depending on applications and often hybridized with other techniques
to improve performance. This also includes some of the variants and hybridized
versionsofpopularlyusedSItechniques.
Ontheapplicationfront,SItechniquesarewidelyusedinoptimizationproblems
indifferentdomains,includingbutnotlimitedtoElectricalandPowerSystems,Elec-
tronicsandCommunicationEngineering,MachineLearning,DeepLearning,Social
Network Analysis, Pattern Recognition, Speech Processing, Image Processing,
Bioinformatics, Health Informatics, Manufacturing and Operation Research, just
tonameafew.ThisbookcomprisessomeofthemajorapplicationsofSItechniques
indifferentdomainsasmentionedabove.Thebookfocusesontheadaptivenature
ofSItechniquesfromthecontextofapplications.Forspecificproblems,howrepre-
sentation of population is done, how objective function is designed, what kind of
changesaredoneinSItechniqueitself,howtodealwithconstraints,howtomanage
conflictingobjectives,alltheseissuesareaddressedinthebookfromtheviewpoint
ofapplications.
This book emphasizes the studies of existing SI techniques, their variants and
applications.ThebookalsocontainsreviewsofnewdevelopmentsinSItechniques
andhybridizations.Algorithm-specificstudiescoveringbasicintroductionandanal-
ysisofkeycomponentsofthesealgorithms,suchasconvergence,balanceofsolu-
tionaccuracy,computationalcosts,tuning,andcontrolofparameters.Application-
specific studies incorporating the ways of designing objective functions, solution
representation,andconstrainthandling.Thebookalsoincludesstudiesonapplication
domain-specificadaptationsintheSItechniques.
v
vi Preface
Thebookisorganizedintofourparts.PartIcoversstateoftheartinSI,which
includesreviewsonSItechniques,variousoptimizationproblems,andperformance
analysis of SI techniques. Part II covers applications of SI techniques in various
engineeringproblems.PartIIIcomprisesapplicationsofSItechniquesindifferent
machinelearningproblemssuchasclusteringandprediction.Thelastpartincludes
severalotherapplicationsofSItechniques.
Wecordiallythankalltheauthorsfortheirvaluablecontributions.Wealsothank
thereviewersfortheirinputandvaluablesuggestions.
Finally,wethankallthestakeholderswhohavecontributeddirectlyorindirectly
tomakingthisbookasuccess.
Silchar,India AnupamBiswas
Pamukkale,Turkey CanB.Kalayci
Brisbane,Australia SeyedaliMirjalili
March2022
Contents
State-of-the-Art
A Brief Tutorial on Optimization Problems, Optimization
Algorithms,Meta-Heuristics,andSwarmIntelligence ................. 3
SeyedaliMirjalili,CanB.Kalayci,andAnupamBiswas
IntroductoryReviewofSwarmIntelligenceTechniques ............... 15
ThounaojamChinglemba, SoujanyoBiswas, DebashishMalakar,
VivekMeena,DebojyotiSarkar,andAnupamBiswas
Swarm Intelligence for Deep Learning: Concepts, Challenges
andRecentTrends ................................................. 37
VandanaBharti,BhaskarBiswas,andKaushalKumarShukla
AdvancesonParticleSwarmOptimizationinSolvingDiscrete
OptimizationProblems ............................................ 59
M.A.H.Akhand,Md.MasudurRahman,andNazmulSiddique
Performance Analysis of Hybrid Memory Based Dragonfly
AlgorithminEngineeringProblems ................................. 89
SanjoyDebnath,RaviSinghKurmvanshi,andWasimArif
EngineeringProblems
Optimum Design and Tuning Applications in Structural
EngineeringviaSwarmIntelligence ................................. 109
GebrailBekdas¸,SinanMelihNigdeli,andAylinEceKayabekir
BeeColonyOptimizationwithApplicationsinTransportation
Engineering ....................................................... 135
DušanTeodorovic´,MilošNikolic´,MilicaŠelmic´,andIvanaJovanovic´
ApplicationofSwarmBasedApproaches forElasticModulus
PredictionofRecycledAggregateConcrete .......................... 153
HarishNarayanaandPrashanthJanardhan
vii
viii Contents
GreyWolfOptimizer,WhaleOptimizationAlgorithm,andMoth
FlameOptimizationforOptimizingPhotonicsCrystals ............... 169
SeyedMohammadMirjalili, SeyedehZahraMirjalili,
NimaKhodadadi,VaclavSnasel,andSeyedaliMirjalili
Intelligent and Reliable Cognitive 5G Networks Using Whale
OptimizationTechniques ........................................... 181
JasiyaBashir,JavaidAhmadSheikh,andZahidA.Bhat
MachineLearning
AutomaticDataClusteringUsingFarmlandFertilityMetaheuristic
Algorithm ........................................................ 199
FarhadSoleimanianGharehchopoghandHumanShayanfar
A Comprehensive Review of the Firefly Algorithms for Data
Clustering ........................................................ 217
MKAAriyaratneandTGIFernando
AHybridAfricanVultureOptimizationAlgorithmandHarmony
Search:AlgorithmandApplicationinClustering ..................... 241
FarhadSoleimanianGharehchopogh, BenyaminAbdollahzadeh,
NimaKhodadadi,andSeyedaliMirjalili
EstimationModelsforOptimumDesignofStructuralEngineering
ProblemsviaSwarm-IntelligenceBasedAlgorithmsandArtificial
NeuralNetworks .................................................. 255
MeldaYücel,SinanMelihNigdeli,andGebrailBekdas¸
A Novel Codebook Generation by Lévy Flight Based Firefly
Algorithm ........................................................ 269
IlkerKilic
Novel Chaotic Best Firefly Algorithm: COVID-19 Fake News
DetectionApplication .............................................. 285
MiodragZivkovic, AleksandarPetrovic, K.Venkatachalam,
IvanaStrumberger,HothefaShakerJassim,andNebojsaBacanin
OtherApplications
ArtificialBeeColonyandGeneticAlgorithmsforParameters
EstimationofWeibullDistribution .................................. 309
MuhammetBurakKılıç
GraphStructureOptimizationforAgentControlProblemsUsing
ACO ............................................................. 327
MohamadRoshanzamir,MahdiRoshanzamir,NavidHoseiniIzadi,
andMaziarPalhang
Contents ix
ABumbleBeesMatingOptimizationAlgorithmfortheDiscrete
andDynamicBerthAllocationProblem ............................. 347
EleftheriosTsakirakis,MagdaleneMarinaki,andYannisMarinakis
Applying the Population-Based Ant Colony Optimization
totheDynamicVehicleRoutingProblem ............................ 369
MichalisMavrovouniotis, GeorgiosEllinas, IaêS.Bonilha,
FelipeM.Müller,andMariosPolycarpou
AnImprovedCuckooSearchAlgorithmfortheCapacitatedGreen
VehicleRoutingProblem ........................................... 385
KenanKaragulandYusufSahin
Multi-ObjectiveArtificialHummingbirdAlgorithm .................. 407
NimaKhodadadi, SeyedMohammadMirjalili, WeiguoZhao,
ZhenxingZhang,LiyingWang,andSeyedaliMirjalili
