Multi-Objective Optimization in Chemical Engineering: Developments and Applications

514 Pages·2013·5.849 MB·English

Multi-Objective Optimization
in Chemical Engineering
Multi-Objective
Optimization in
Chemical Engineering
Developments and Applications
Edited by
GADE PANDU RANGAIAH
Department of Chemical and Biomolecular Engineering,
National University of Singapore, Singapore
ADRIA´N BONILLA-PETRICIOLET
Department of Chemical Engineering,
Instituto Tecnolo´gico de Aguascalientes, Mexico
A John Wiley & Sons, Ltd., Publication
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LibraryofCongressCataloging-in-PublicationData
Multi-objectiveoptimizationinchemicalengineering:developmentsandapplications/[editedby]GadeRangaiah,Adria´n
Bonilla-Petriciolet.
pages cm
ISBN978-1-118-34166-7(hardback)
1.Chemicalprocesses. 2.Mathematicaloptimization. 3.Chemicalengineering. I.Rangaiah,GadePandu.
II.Bonilla-Petriciolet,Adria´n.
TP155.7.M6452013
660–dc23
2012048233
AcataloguerecordforthisbookisavailablefromtheBritishLibrary
ISBN:9781118341667
Setin10/12ptTimesbyAptaraInc.,NewDelhi,India
Contents
ListofContributors xiii
Preface xv
Part I Overview 1
1 Introduction 3
Adria´nBonilla-PetricioletandGadePanduRangaiah
1.1 OptimizationandChemicalEngineering 3
1.2 BasicDefinitionsandConceptsofMulti-ObjectiveOptimization 5
1.3 Multi-ObjectiveOptimizationinChemicalEngineering 8
1.4 ScopeandOrganizationoftheBook 9
References 15
2 OptimizationofPoolingProblemsforTwoObjectivesUsingthe
ε-ConstraintMethod 17
HaiboZhangandGadePanduRangaiah
2.1 Introduction 17
2.2 PoolingProblemDescriptionandFormulations 19
2.2.1 p-Formulation 19
2.2.2 r-Formulation 21
2.3 ε-ConstraintMethodandIDEAlgorithm 25
2.4 ApplicationtoPoolingProblems 27
2.5 ResultsandDiscussion 28
2.6 Conclusions 32
Exercises 33
References 33
3 Multi-ObjectiveOptimizationApplicationsinChemicalEngineering 35
ShivomSharmaandGadePanduRangaiah
3.1 Introduction 35
3.2 MOOApplicationsinProcessDesignandOperation 37
3.3 MOOApplicationsinPetroleumRefining,Petrochemicalsand
Polymerization 57
vi Contents
3.4 MOOApplicationsintheFoodIndustry,Biotechnologyand
Pharmaceuticals 57
3.5 MOOApplicationsinPowerGenerationandCarbonDioxide
Emissions 66
3.6 MOOApplicationsinRenewableEnergy 66
3.7 MOOApplicationsinHydrogenProductionandFuelCells 82
3.8 Conclusions 82
Acronyms 87
References 87
Part II Multi-ObjectiveOptimizationDevelopments 103
4 PerformanceComparisonofJumpingGeneAdaptationsoftheElitist
Non-dominatedSortingGeneticAlgorithm 105
ShivomSharma,SeyedRezaNabaviandGadePanduRangaiah
4.1 Introduction 105
4.2 JumpingGeneAdaptations 107
4.3 TerminationCriterion 110
4.4 ConstraintHandlingandImplementationofPrograms 112
4.5 PerformanceComparison 114
4.5.1 PerformanceComparisononUnconstrainedTestFunctions 114
4.5.2 PerformanceComparisononConstrainedTestFunctions 121
4.6 Conclusions 124
Exercises 124
References 125
5 ImprovedConstraintHandlingTechniqueforMulti-Objective
OptimizationwithApplicationtoTwoFermentationProcesses 129
ShivomSharmaandGadePanduRangaiah
5.1 Introduction 129
5.2 ConstraintHandlingApproachesinChemicalEngineering 131
5.3 AdaptiveConstraintRelaxationandFeasibilityApproachforSOO 132
5.4 AdaptiveRelaxationofConstraintsandFeasibilityApproachforMOO 133
5.5 TestingofMODE-ACRFA 136
5.6 Multi-ObjectiveOptimizationoftheFermentationProcess 139
5.6.1 Three-StageFermentationProcessIntegratedwithCell
Recycling 139
5.6.2 Three-StageFermentationProcessIntegratedwithCell
RecyclingandExtraction 145
5.6.3 GeneralDiscussion 152
5.7 Conclusions 153
Acronyms 153
References 154
Contents vii
6 RobustMulti-ObjectiveGeneticAlgorithm(RMOGA)withOnline
ApproximationunderIntervalUncertainty 157
WeiweiHu,AdeelButt,AliAlmansoori,ShapourAzarmandAliElkamel
6.1 Introduction 157
6.2 BackgroundandDefinition 159
6.2.1 Multi-ObjectiveGeneticAlgorithm(MOGA) 160
6.2.2 Multi-ObjectiveRobustnesswithIntervalUncertainty:
BasicIdea 161
6.3 RobustMulti-ObjectiveGeneticAlgorithm(RMOGA) 163
6.3.1 NestedRMOGA 163
6.3.2 SequentialRMOGA 165
6.3.3 ComparisonbetweenNestedandSequentialRMOGA 167
6.4 OnlineApproximation-AssistedRMOGA 168
6.4.1 StepsinApproximation-AssistedRMOGA 168
6.4.2 Sampling 169
6.4.3 MetamodelingandVerification 170
6.4.4 SampleSelectionandFiltering 171
6.5 CaseStudies 172
6.5.1 NumericalExample 172
6.5.2 OilRefineryCaseStudy 175
6.6 Conclusions 178
References 179
7 ChanceConstrainedProgrammingtoHandleUncertainty
inNonlinearProcessModels 183
KishalayMitra
7.1 Introduction 183
7.2 UncertaintyHandlingTechniques 184
7.3 Chance-ConstrainedProgramming:Fundamentals 186
7.3.1 CalculationofP(hk(cid:2)(x(cid:3),ξ(cid:2))≥0)≥p (cid:4)(k=(cid:4)1,...,u) 192
7.3.2 Calculationofmax f˜(cid:3)P f(x,ξ)≥f˜ ≥α 193
7.4 IndustrialCaseStudy:Grinding 193
7.4.1 GrindingProcessandModeling 193
7.4.2 OptimizationFormulation 195
7.4.3 ResultsandDiscussion 199
7.5 Conclusions 206
Nomenclature 209
Appendices 210
A.1 CCPforNormallyDistributedUncertainParameters 210
A.2 CalculationofMeanandVarianceforGeneralFunction 212
References 212
viii Contents
8 FuzzyMulti-ObjectiveOptimizationforMetabolicReactionNetworks
byMixed-IntegerHybridDifferentialEvolution 217
Feng-ShengWangandWu-HsiungWu
8.1 Introduction 217
8.2 ProblemFormulation 219
8.2.1 PrimalMulti-ObjectiveOptimizationProblem 219
8.2.2 ResilienceProblem 221
8.3 Optimality 223
8.4 Mixed-IntegerHybridDifferentialEvolution 228
8.4.1 Algorithm 228
8.4.2 ConstraintHandling 231
8.5 Examples 233
8.6 Conclusions 240
Exercises 241
References 242
Part III ChemicalEngineeringApplications 247
9 ParameterEstimationinPhaseEquilibriaCalculations
UsingMulti-ObjectiveEvolutionaryAlgorithms 249
SameerPunnapala,FranciscoM.VargasandAliElkamel
9.1 Introduction 249
9.2 ParticleSwarmOptimization(PSO) 250
9.2.1 Multi-ObjectiveParticleSwarmOptimization(MO-PSO) 251
9.3 ParameterEstimationinPhaseEquilibriaCalculations 253
9.4 ModelDescription 253
9.4.1 VaporLiquidEquilibrium 254
9.4.2 HeatofMixing 255
9.5 Multi-ObjectiveOptimizationResultsandDiscussion 257
9.6 Conclusions 260
Nomenclature 260
Exercises 261
References 264
10 PhaseEquilibriumDataReconciliationUsingMulti-Objective
DifferentialEvolutionwithTabuList 267
Adria´nBonilla-Petriciolet,ShivomSharmaandGadePanduRangaiah
10.1 Introduction 267
10.2 FormulationoftheDataReconciliationProblemforPhase
EquilibriumModeling 270
10.2.1 DataReconciliationProblem 270
10.2.2 DataReconciliationforPhaseEquilibriumModeling 271
10.3 Multi-ObjectiveOptimizationusingDifferentialEvolutionwith
TabuList 274
Contents ix
10.4 DataReconciliationofVapor-LiquidEquilibriumbyMOO 277
10.4.1 DescriptionoftheCaseStudy 277
10.4.2 DataReconciliationResults 278
10.5 Conclusions 287
Exercises 290
References 290
11 CO EmissionsTargetingforPetroleumRefineryOptimization 293
2
MohmmadA.Al-Mayyahi,AndrewF.A.HoadleyandGadePanduRangaiah
11.1 Introduction 293
11.1.1 OverviewoftheCDU 295
11.1.2 OverviewoftheFCC 296
11.1.3 PinchAnalysis 297
11.1.4 Multi–ObjectiveOptimization(MOO) 301
11.2 MOO-PinchAnalysisFrameworktoTargetCO Emissions 303
2
11.3 CaseStudies 304
11.3.1 CaseStudy1:DirectHeatIntegration 305
11.3.2 CaseStudy2:TotalSiteHeatIntegration 310
11.4 Conclusions 315
Nomenclature 315
Exercises 317
Appendices 318
A.1 ModelingofCDUandFCC 318
A.2 PreliminaryResultswithDifferentValuesforNSGA-IIParameters 320
A.3 PinchAnalysisTechniques 320
A.3.1 CompositeCurves(CC) 322
A.3.2 GrandCompositeCurve(GCC) 326
A.3.3 TotalSiteProfiles 326
References 331
12 EcodesignofChemicalProcesseswithMulti-ObjectiveGenetic
Algorithms 335
CatherineAzzaro-Pantel,AdamaOuattaraandLucPibouleau
12.1 Introduction 335
12.2 NumericalTools 337
12.2.1 EvolutionaryApproach:Multi-ObjectiveGenetic
Algorithms 337
12.2.2 ChoiceoftheBestSolutions 337
12.3 Williams–OttoProcess(WOP)OptimizationforMultipleEconomic
andEnvironmentalObjectives 338
12.3.1 ProcessModelling 338
12.3.2 OptimizationVariables 339
12.3.3 ObjectivesforOptimization 340
12.3.4 ProblemConstraints 341
x Contents
12.3.5 Implementation 341
12.3.6 ProcedureValidation 341
12.3.7 Tri-ObjectiveOptimization 343
12.3.8 Discussion 346
12.4 RevisitingtheHDAProcess 346
12.4.1 HDAProcessDescriptionandModellingPrinciples 346
12.4.2 OptimizationVariables 349
12.4.3 ObjectiveFunctions 350
12.4.4 Multi-ObjectiveOptimization 354
12.5 Conclusions 361
Acronyms 363
References 364
13 ModelingandMulti-ObjectiveOptimizationofa
ChromatographicSystem 369
AbhijitTarafder
13.1 Introduction 369
13.2 Chromatography—SomeFacts 371
13.3 ModelingChromatographicSystems 373
13.4 SolvingtheModelEquations 376
13.5 StepsforModelCharacterization 377
13.5.1 IsothermsandtheParameters 378
13.5.2 SelectionofIsotherms 379
13.5.3 ExperimentalStepstoGenerateFirstApproximation 382
13.6 DescriptionoftheOptimizationRoutine—NSGA-II 387
13.7 OptimizationofaBinarySeparationinChromatography 387
13.7.1 SelectionoftheObjectiveFunctions 387
13.7.2 SelectionoftheDecisionVariables 388
13.7.3 SelectionoftheConstraints 389
13.8 AnExampleStudy 390
13.8.1 SchemesoftheOptimizationStudies 390
13.8.2 ResultsandDiscussion 393
13.9 Conclusions 396
References 397
14 EstimationofCrystalSizeDistribution:ImageThresholdingBasedon
Multi-ObjectiveOptimization 399
KarthikRajaPeriasamyandS.Lakshminarayanan
14.1 Introduction 399
14.2 Methodology 401
14.3 ImageSimulation 402
14.3.1 CameraModel 402
14.3.2 ProcessModel 402
14.3.3 Assumptions 403
14.4 ImagePreprocessing 404
Contents xi
14.5 ImageSegmentation 404
14.5.1 ImageThresholdingBasedonSingleObjectiveOptimization 404
14.5.2 Multi-ObjectiveOptimization 406
14.5.3 ProblemFormulation 409
14.5.4 ResultsandDiscussion 410
14.6 FeatureExtraction 413
14.6.1 ResultsandDiscussion 414
14.7 FutureWork 417
14.8 Conclusions 418
Nomenclature 418
References 419
15 Multi-ObjectiveOptimizationofaHybridSteamStripper-Membrane
ProcessforContinuousBioethanolPurification 423
KrishnaGudena,GadePanduRangaiahandS.Lakshminarayanan
15.1 Introduction 423
15.2 DescriptionandDesignofaHybridStripper-MembraneSystem 426
15.2.1 HybridStripper-MembraneSystemofHuangetal. 426
15.2.2 ModifiedDesignoftheHybridStripper-MembraneSystem 427
15.3 MathematicalFormulationandOptimization 431
15.3.1 ProblemFormulation 432
15.3.2 OptimizationMethodologyforMOOProblemsin
CasesAandB 434
15.4 ResultsandDiscussion 435
15.4.1 MaximizeEthanolPurity(f )andMinimizeOperating
purity
Cost/kgofBioethanol(f ) 435
cost
15.4.2 MinimizeEthanolLoss(f )andalsoOperatingCost/kgof
loss
Bioethanol(f ) 439
cost
15.4.3 DetailedAnalysisofaSelectedOptimalSolution 440
15.5 Conclusions 445
Exercises 445
References 446
16 ProcessDesignforEconomic,EnvironmentalandSafetyObjectiveswith
anApplicationtotheCumeneProcess 449
ShivomSharma,ZiChaoLimandGadePanduRangaiah
16.1 Introduction 449
16.2 ReviewandCalculationofSafetyIndices 451
16.2.1 IntegratedInherentSafetyIndex(I2SI) 452
16.3 CumeneProcess,itsSimulationandCosting 455
16.4 I2SICalculationforCumeneProcess 459
16.4.1 FEDRCalculationforUnitsInvolvingPhysicalOperations 459
16.4.2 FEDRCalculationforUnitsInvolvingChemicalReactions 460
16.4.3 TDRCalculation 461
16.4.4 ConversionofFEDRtoFEDI,andTDRtoTDI 462