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Nature-InspiredComputing ParadigmsinSystems
Editedby
MohamedArezkiMellal,AssociateProfessor, DepartmentofMechanicalEngineering,FacultyofTechnology,M’HamedBougaraUniversity, Boumerdes,Algeria CALCE(CenterforAdvancedLifeCycleEngineering),UniversityofMaryland,CollegePark,MD, UnitedStates
MichaelG.Pecht,Professor, CALCE(CenterForAdvancedLifeCycleEngineering),UniversityofMaryland, CollegePark,MD,UnitedStates
SeriesEditor:FatosXhafa UniversitatPolite ` cnicadeCatalunya,Spain
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Contributors
RoumaissaBoutiche
LMSS,FacultyofTechnology,M’HamedBougaraUniversity,Boumerdes,Algeria
NarimanL.Dehghani
RiskAssessmentandManagementofStructuralandInfrastructureSystems(RAMSISlab), TheOhioStateUniversity,Columbus,OH,UnitedStates
MohammadAliFarsi
Reliabilityandstandardgroup,A&SResearchInstitute,MinistryofScience,Researchand Technology,Tehran,Iran
AbirFrik
LMSS,FacultyofTechnology,M’HamedBougaraUniversity,Boumerdes,Algeria
IkramHamadache
LMSS,FacultyofTechnology,M’HamedBougaraUniversity,Boumerdes,Algeria
KaiHe
SchoolofEngineeringScience,UniversityofScienceandTechnologyofChina,Hefei,China
KasunHewage
SchoolofEngineering,UniversityofBritishColumbia,OkanaganCampus,Kelowna,BC,Canada
LisaJackson
DepartmentofAeronauticalandAutomotiveEngineering,LoughboroughUniversity, Loughborough,UnitedKingdom
AmitKumar
DepartmentofInformationTechnology,RajkiyaEngineeringCollege,AmbedkarNagar,Akbarpur, UttarPradesh,India
LeiMao
SchoolofEngineeringScience,UniversityofScienceandTechnologyofChina,Hefei,China
MohamedArezkiMellal
LMSS,FacultyofTechnology,M’HamedBougaraUniversity,Boumerdes,Algeria;Center forAdvancedLifeCycleEngineering(CALCE),UniversityofMaryland,CollegePark,MD, UnitedStates
RachidOuache
SchoolofEngineering,UniversityofBritishColumbia,OkanaganCampus,Kelowna,BC,Canada
RehanSadiq
SchoolofEngineering,UniversityofBritishColumbia,OkanaganCampus,Kelowna,BC,Canada
LaxminarayanSahoo
DepartmentofComputerandInformationScience,RaiganjUniversity,Raiganj,India
AbdollahShafieezadeh
RiskAssessmentandManagementofStructuralandInfrastructureSystems(RAMSISlab), TheOhioStateUniversity,Columbus,OH,UnitedStates
Contributors
AminMohammadpourShotorbani
SchoolofEngineering,UniversityofBritishColumbia,OkanaganCampus,Kelowna,BC,Canada
QiangWu
SchoolofEngineeringScience,UniversityofScienceandTechnologyofChina,Hefei,China
ChiZhang
RiskAssessmentandManagementofStructuralandInfrastructureSystems(RAMSISlab), TheOhioStateUniversity,Columbus,OH,UnitedStates
Editorbiographies
MohamedArezkiMellal isanassociateprofessorattheDepartmentofMechanicalEngineering, FacultyofTechnology,M’HamedBougaraUniversity,Algeria,andavisitingscholarattheCenter forAdvancedLifeCycleEngineering,DepartmentofMechanicalEngineering,Universityof Maryland,CollegePark,MD,UnitedStates.Likewise,hewasavisitingscholaratvariousuniversities. Hehaspublishedinseveraljournalsandconferenceproceedings.Hehaseditedfivebooksand authoredsevenbookchapters.HeisamemberoftheAlgerianNationalLaboratoryforMaintenance EducationinconjunctionwiththeEuropeanUnion(Erasmus+).Hehasalsobeenacommitteemember formorethan70internationalconferences.Heservesasaregularreviewerfor18SCI-indexedjournals andaneditorialboardmemberin7peer-reviewedinternationaljournals.Hisresearchinterestsinclude developingnewbioinspiredoptimizationmethodsforsolvingengineeringproblemsofsystemdependability,manufacturing,andenergyefficiency.
MichaelG.Pecht (30,000+citations,80+H-Index)hasaBSinphysics,anMSinelectrical engineering,andanMSandPhDinengineeringmechanicsfromtheUniversityofWisconsin.He isaprofessionalengineer,anIEEEfellow,aPHMSocietylifefellow,anASMEfellow,anASMfellow,anSAEfellow,andanIMAPSfellow.HeservedaseditorinchiefofIEEEAccessfor6years,as editorinchiefofIEEETransactionsonReliabilityfor9years,editorinchiefofMicroelectronics Reliabilityfor16years,andeditorofCircuitWorld.HehasalsoservedonthreeUSNationalAcademy ofSciencestudies,twoUSCongressionalinvestigationsinautomotivesafety,andasanexperttothe USFDA.HeistheDirectorofCenterforAdvancedLifeCycleEngineering(CALCE)attheUniversity ofMaryland(UMd),whichisfundedbymorethan150world’sleadingelectronicscompaniesatmore thanUS$6M/year.HeisalsoaprofessorinappliedmathematicsatUMD.In2008,hewasawardedthe highestreliabilityhonor,theIEEEReliabilitySociety’sLifetimeAchievementAward.In2010,he receivedtheIEEEExceptionalTechnicalAchievementAwardforhisinnovationsintheareaof prognosticsandsystemshealthmanagement.
Preface
Nowadays,competitivenessinallindustrialsectorsisduetothenumberofcompaniesandtherequirementsofregulationsandusers.Industrialcompaniesfocusondevelopmentandacquisitionofsystems withahighlevelofdependability.However,itinvolvesmanychallenges.Duringthelastdecades,varioussolutiontechniqueshavebeenproposedtodealwiththesechallenges.Nature-inspiredcomputing techniqueshaveprovedtheireffectivenessinsolvinghardengineeringproblems.Thepresentworkis partofnature-inspiredparadigmsinsystems—RAMS+C(Reliability,Availability,Maintainability, Safety,andCost)&PHM(PrognosticsandHealthManagement).
Thebookisdividedintoeightchapters. Chapter1 dealswiththereliabilityoptimizationofasafety systeminthepowerplantusinggraywolfoptimizerandtheshuffledflog-leapingalgorithm. Chapter2 addressesthedesignoptimizationofthecarsidesafetysystemusingparticleswarmoptimizationand graywolfoptimizer. Chapter3 presentsthebasicprinciplesofgeneticalgorithmanditsapplicationin RAMS. Chapter4 usesevolutionaryoptimizationforresilience-basedplanninginpowerdistribution networks. Chapter5 presentsareviewoftheapplicationofnature-inspiredcomputinginoptimaldesign. Chapter6 usesartificialneuralnetworksandgeneticalgorithmsforfiresafetystrategiesassessment. Chapter7 appliesartificialneuralnetworkstoprotonexchange.Finally, Chapter8 addresses reliabilityredundancyallocationproblemswithuncertaintiesusinggeneticalgorithmsanddualconnectionnumbers.
Thisbookcanbeusedbyresearchers,students,engineers,industrialcompanies,oranypersoninterestedinnature-inspiredcomputationandRAMS+C&PHM.
MohamedArezkiMellal
MichaelG.Pecht
Acknowledgment
Theeditorswouldliketothankthefollowingreviewers:
FaustoPedroGarcı´aMa ´ rquez UniversidadCastilla-LaMancha,Spain
HarishGarg
ThaparInstituteofEngineeringandTechnology,India
PaymanDehghanian GeorgeWashingtonUniversity,UnitedStates
SameerAl-Dahidi GermanJordanianUniversity,Jordan
WeiWang CityUniversityofHongKong,HongKong
Reliabilityoptimizationofpower plantsafetysystemusinggreywolf optimizerandshuffledfrog-leaping algorithm
MohamedArezkiMellala,b,AbirFrika,andRoumaissaBoutichea LMSS,FacultyofTechnology,M’HamedBougaraUniversity,Boumerdes,Algeriaa CenterforAdvancedLifeCycle Engineering(CALCE),UniversityofMaryland,CollegePark,MD,UnitedStatesb
1. Introduction
Theworldiswitnessinggreatindustrialdevelopmentsinwhichtheneedforhigh-leveloperatingfacilitiesleadstogreatcompetition.Inthiscontext,thedesignersmustdevotetheireffortstoincreasethe reliabilityofthesystemstoincreasetheoverallreliabilityofthefacilities.Themostcommondesign objectivesare(1)themaximizationofthesystemreliabilityundertheallowablesystemcostandother designlimits,suchastheweightandvolume;(2)theminimizationofthesystemcostundertheallowablesystemreliabilityandtheotherdesignlimitsforthesingle-objectivereliabilityoptimizationproblems(ROPs);or(3)acombinationofconsiderations,suchassystemreliabilityandcostforthe multiobjectiveROPs.Systemreliabilitycouldbeimprovedusingthreemainmethods:
1. Redundancyallocation:addredundantcomponentsinparallel.Thismethodcouldbeemployed usingactiveorstandbycomponents.Ifthestandbyredundantcomponentscannotfailuntiltheyare switchedon,thenitiscalledcold-standbystrategy [1,2].Ifthestandbyredundantcomponentscan failwhentheyareswitchedoffandhavelowerfailureratesthantheactivecomponents,itiscalled warm-standbystrategy.Insomereferences,theactivecomponentredundancystrategyiscalledhotstandbystrategy [3,4].
2. Reliabilityallocation:allocatereliabilitytothecomponentsand/orsubsystemsofthesystemto meettheoverallrequiredsystemreliability.
3. Reliability-redundancyallocation:acombinationoftheallocations1and2.
Thischapterfocusesonthesingle-objectiveROPs.Thereliability-redundancyoptimizationproblemof apowerplantsafetysystemisaddressedusingthegreywolfoptimizer(GWO)andtheshuffledfrogleapingalgorithm(SFLA).Itisorganizedasfollows: Section2 givesaliteraturereviewofsomepreviousworksrelatedtotheROPs. Section3 presentstheROPoftheinvestigatedpowerplantsafety
system.TheimplementedGWOandSFLAarepresentedin Sections4and5,respectively. Section6 discussestheresultsobtained.Finally,thelastsectionconcludesthechapter.
2. Literaturereview
SeveralresearchworkshavebeendevotedtotheROPs.Refs. [5–7] areamongthefirstpaperspublishedonthistopicandtheauthorsusedtheso-calledclassicalmathematicalmethodtosolvetheROPs. Duringthelastdecades,mostofthesolutionapproacheswerebasedoniterativecomputationalintelligencemethodsthatoffermanyadvantages,suchastheabilitytohandlehardproblems,flexibility, goodresults,andreasonablecomputationaltime [8–12].SeveralROPswerereviewedinRefs. [13,14] Thissectionpresentsanonexecutivereviewoftheliteratureduetothenumberofpublishedworks relatedtothistopic.
Bicking [15] proposedasolutionmethodbasedongeneticalgorithmswithevolutionarystrategies (GMs).Thismethodcombinestheprincipleoftrackingthemostsuitableindividualsandthegenetic combinationsforanelitistresearchmechanism.Toprovetheperformanceoftheproposedmethod, foursystemswithvariousconfigurationswereinvestigatedandtheresultswerecomparedtothose ofthesimulatedannealing(SA);itsvariant,animprovednonequilibriumsimulatedannealing (I-NESA);andthefuzzyglobaloptimization(FO).TheresultsshowedthattheGMisnotsuperior butverychallengingwiththeotherappliedmethods.AgarwalandSharma [16] usedthebasicantcolonyoptimization,includinganadaptivepenaltyfunction,tohandlethedesignconstraints(ASACO) andtheresultsobtainedwerecomparedtothoseobtainedbythegeneticalgorithms(GAs)withadynamicadaptivepenaltystrategyproposedinRef. [17].Zouetal. [18] proposedanovelmodifieddifferentialevolution(NMDE).TheNMDEwastestedontheROPsofthecomplex(bridge)andthe overspeedprotectionsystems.Theresultsobtainedshowedthatineachproblem,theNMDEissuperior tothreeothersolutionapproachesavailableintheliterature.Garg [19] usedthecuckoosearch(CS) withapenaltyfunction.Itwastestedover25independentrunsinsolvingvariousROPsandtheresults werepromisingcomparedtoseveralworksavailableintheliterature.MellalandZio [20] proposeda penalty-guidedstochasticfractalsearch(PSFS)forsolvingthethreemethodsofsystemreliabilityoptimization.TencasestudiesweresolvedusingthePSFSandtheresultsobtainedwerebetterthanthose of36methodsappliedintheliterature.Also,inRef. [21],thePSFSshoweditssuperiorityovertheGA andthecuckoooptimizationalgorithmwithpenaltyfunction(PFCOA)insolvingthereliabilityoptimizationofasystemcontaining30subsystemsconnectedinseries.MellalandWilliams [22] implementedtheGA,particleswarmoptimization(PSO),andthecuckoooptimizationalgorithm(COA)to solveasysteminvolving20subsystemsinseries.TheCOAhasoutperformedtheGAandthePSO. MellalandZio [23] proposedanadaptiveparticleswarmoptimization(ADAP-PSO)toconsider thesystemreliability,cost,weight,andvolumeasobjectives.Themultiobjectiveoptimizationproblem hasbeenconvertedtoasingle-objectiveproblemusingaweightedsummethod.Theresultsshowed thattheADAP-PSOperformsbetterthanthePSO.Taghiyehetal. [24] consideredtheparameteruncertaintiesintheROPsusingfuzzynumbertheories.Sharma [25] proposedabidirectionalbutterfly optimizationalgorithm(BBOA)andshowedthatitperformsbetterthantheBOA.InRefs. [1,2, 26,27],theauthorsaddressedtheROPswiththecold-standbystrategyusingtheintegerprogramming [1],GAs [26],SFS [27],andenhancednestcuckoooptimizationalgorithm(ENCOA) [2].
Dobanietal. [28] proposedusingheterogeneousredundantcomponentsintheROPs.Ithasbeenproven thatthisstrategyincreasesthesystemreliabilitycomparedtosystemswithhomogeneous components.AhybridsolutionapproachbasedontheSFSandtheGA(SFS-GA)wasproposedtosolve theproblem.Mellaletal. [29] proposedahostedcuckoooptimizationalgorithm(HO-COA)tosolve thistypeofROPmoreeffectively.TheresultsshowedthattheHO-COAperformsbetterthanthe SFS-GA,COA,differentialevolution(DE),andflowerpollinationalgorithm(FPA).Ouyangetal. [30] addressedamixedredundancystrategy(activeandcold-standbyredundantcomponents)withheterogeneouscomponentsandsolvedtheproblemusingthePSOwithstochasticperturbationnature (SPPSO).Theresultsshowedthatthisstrategyreachesbetterreliabilitythanthemixedredundancy strategywithhomogeneouscomponents. Table1 summarizestheworksreviewedinthissection.
Table1Summaryofthelistedpreviousworks.
[5] DynamicprogrammingXActive, homogeneous components
[6] IntegerprogrammingXActive, homogeneous components
[7] ComputationalprocedureXActive, homogeneous components
[15] Geneticalgorithmswith evolutionarystrategies(GMs) XXActive, homogeneous components
[16] Antcolonyoptimizationwithan adaptivepenaltyfunction (ASACO) XActive, homogeneous components
[17] Geneticalgorithmswith dynamicadaptivepenalty strategy(GAs)
homogeneous components
[18] Novelmodifieddifferential evolution(NMDE) XActive, homogeneous components
[19] Cuckoosearchwithapenalty function(CS)
[20] Penalty-guidedstochastic fractalsearch(PSFS)
homogeneous components
homogeneous components
Table1Summaryofthelistedpreviousworks—cont’d
ReferenceMethod
[21] Penalty-guidedstochastic fractalsearch(PSFS)
XActive, homogeneous components
[22] Cuckoooptimizationalgorithm (COA) XActive, homogeneous components
[23] Adaptiveparticleswarm optimization(ADAP-PSO)
XXActive, homogeneous components
[24] α-levelcutsXActive, homogeneous components
[25] Bidirectionalbutterfly optimizationalgorithm(BBOA) XXActive, homogeneous components
[1] IntegerprogrammingXCold-standby, homogeneous components
[2] Enhancednestcuckoo optimizationalgorithm (ENCOA)
XCold-standby, homogeneous components
[26] Modifiedversionofthegenetic algorithm(GA) XCold-standby, homogeneous components
[27] Penalty-guidedfractalsearch algorithm(SFS)
XCold-standby, homogeneous components
[28] Hybridstochasticfractalsearch withgeneticalgorithms (hSFS-GA) XActive, heterogeneous components
[29] Hostedcuckoooptimization algorithm(HO-COA)
[30] Particleswarmoptimization withstochasticperturbation nature(SPPSO)
3. Problemdescription
XActive, heterogeneous components
XMixed, heterogeneous components
Theoverspeedprotectionsystemcontainsmechanicalandelectricalsystemsthatprotectthegasturbineinthepowerplant.Itinvolves4-stagecontrolvalves(V1–V4)connectedinseries(see Fig.1, [20, 31–33]).Thereliability-redundancyallocationproblemwasinitiallydescribedbyDhingra [34]:
FIG.1
Overspeedprotectionsystem.
subjectto
where Rs(r,n)isthereliabilityoftheoverspeedprotectionsystem, r isthevectorofthecontrolvalves’ reliabilities, n isthevectorofthenumberofredundantcontrolvalves, ri isthereliabilityofthecontrol valveatstage i, ni isthenumberofredundantcontrolvalvesatstage i, τ and ζ arethephysicalcharacteristicsofeachcontrolvalveateachstage, T isthemissiontime, vi isthevolumeofeachcontrol valveatstage i, wi istheweightofeachcontrolvalveatstage i, R istheminimumallowablesystem reliability, V isthemaximumallowablevolume, C isthemaximumcost,and W isthemaximumweight. Table2 reportsthedataofthesystem,wherethecost,volume,andweightaregiveninarbitraryunits.
Table2Dataofthesystem.
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