An introduction to management science : quantitative approaches to decision making.

708 Pages·2014·10.57 MB·English

by  David Ray Anderson

David R. Anderson Dennis J. Sweeney
l
Thomas A. Williams Mik Wisniewski
l
AN INTRODUCTION TO
MANAGEMENT
SCIENCE
QUANTITATIVE APPROACHES
TO DECISION MAKING
second edition
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QuantitativeApproachestoDecision
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Brief contents
AbouttheAuthors xi
Preface xiii
Acknowledgements xv
1 Introduction 1
2 An Introduction to Linear Programming 33
3 Linear Programming: Sensitivity Analysis and Interpretation of Solution 85
4 Linear Programming Applications 137
5 Linear Programming: The Simplex Method 211
6 Simplex-Based Sensitivity Analysis and Duality 254
7 Transportation, Assignment and Transshipment Problems 279
8 Network Models 344
9 Project Scheduling: PERT/CPM 370
10 Inventory Models 405
11 Queuing Models 451
12 Simulation 489
13 Decision Analysis 539
14 Multicriteria Decisions 593
Conclusion:ManagementScienceinPractice 635
Appendices 639
AppendixAAreasfortheStandardNormalDistribution 641
AppendixBValuesofe(cid:2)l 642
AppendixCBibliographyandReferences 643
AppendixDSelf-TestSolutions 645
Glossary 677
Index 683
ONLINECONTENTS
15 Integer Linear Programming
16 Forecasting
17 Dynamic Programming
18 Markov Processes
iii
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deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Contents
AbouttheAuthors xi Simulation 21
Preface xiii DecisionAnalysis 21
Acknowledgements xv Multicriteriaanalysis 21
IntegerLinearProgramming 21
Forecasting 21
1 Introduction 1 DynamicProgramming 22
MarkovProcessModels 22
1.1 IntroductiontoManagementScience 2
Summary 22
DoesitWork? 2
WorkedExample 22
1.2 WhereDidMSComeFrom? 4 Problems 24
1.3 ManagementScienceApplications 5 CaseProblem UhuruCraftCooperative,Tanzania 27
Assignment 5 Appendix1.1 UsingExcelforBreakevenAnalysis 27
DataMining 5 Appendix1.2 TheManagementScientistSoftware 30
FinancialDecisionMaking 6
Forecasting 6 2 An Introduction to Linear
Logistics 6
Programming
33
Marketing 6
Networks 6 2.1 AMaximizationProblem 35
Optimization 7 ProblemFormulation 36
ProjectPlanningandManagement 7 MathematicalStatementoftheGulfGolf
Queuing 7 Problem 39
Simulation 7
2.2 GraphicalSolutionProcedure 40
Transportation 8
ANoteonGraphingLines 48
1.4 TheMSApproach 8 SummaryoftheGraphicalSolutionProcedurefor
ProblemRecognition 9 MaximizationProblems 50
ProblemStructuringandDefinition 9 SlackVariables 51
ModellingandAnalysis 10
2.3 ExtremePointsandtheOptimalSolution 53
SolutionsandRecommendations 11
2.4 ComputerSolutionoftheGulfGolfProblem 54
Implementation 11
InterpretationofComputerOutput 55
1.5 Models 12
2.5 AMinimizationProblem 57
1.6 ModelsofCost,RevenueandProfit 15
SummaryoftheGraphicalSolutionProcedurefor
CostandVolumeModels 15
MinimizationProblems 58
RevenueandVolumeModels 16
SurplusVariables 59
ProfitandVolumeModels 17
ComputerSolutionoftheM&DChemicals
BreakevenAnalysis 17
Problem 61
1.7 TheModellingProcess 18
2.6 SpecialCases 62
1.8 ManagementScienceModelsand AlternativeOptimalSolutions 62
Techniques 20 Infeasibility 63
LinearProgramming 20 UnboundedProblems 64
TransportationandAssignment 20
2.7 GeneralLinearProgrammingNotation 66
NetworkModels 20
Summary 67
ProjectManagement 20
WorkedExample 68
InventoryModels 21
Problems 71
QueuingModels 21
v
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vi CONTENTS
CaseProblem1WorkloadBalancing 76 4.5 FinancialApplications 168
CaseProblem2ProductionStrategy 77 PortfolioSelection 170
CaseProblem3Blending 78 FinancialPlanning 174
Appendix2.1 SolvingLinearProgrammesWithExcel 79 RevenueManagement 178
Appendix2.2 SolvingLinearProgrammesWiththe 4.6 DataEnvelopmentAnalysis 182
ManagementScientist 82
Summary 190
Problems 191
3 Linear Programming: Sensitivity
CaseProblem1PlanninganAdvertising
Analysis and Interpretation of Campaign 200
CaseProblem2PhoenixComputer 202
Solution
85
CaseProblem3TextileMillScheduling 202
3.1 IntroductiontoSensitivityAnalysis 86 CaseProblem4WorkforceScheduling 204
CaseProblem5CinergyCoalAllocation 205
3.2 GraphicalSensitivityAnalysis 88
Appendix4.1 ExcelSolutionofHewlittCorporation
ObjectiveFunctionCoefficients 88
FinancialPlanningProblem 207
Right-HandSides 93
3.3 SensitivityAnalysis:ComputerSolution 97
InterpretationofComputerOutput 97
5 Linear Programming: The
SimultaneousChanges 99
Simplex Method
InterpretationofComputerOutput–ASecond 211
Example 101
5.1 AnAlgebraicOverviewoftheSimplex
CautionaryNoteontheInterpretationofDual
Method 212
Prices 104
AlgebraicPropertiesoftheSimplex
3.4 MorethanTwoDecisionVariables 105 Method 213
TheModifiedGulfGolfProblem 106
DeterminingaBasicSolution 213
TheKenyaCattleCompanyProblem 109
BasicFeasibleSolution 214
FormulationoftheKCCProblem 111
5.2 TableauForm 216
ComputerSolutionandInterpretationfortheKCC
Problem 112 5.3 SettingUptheInitialSimplex
Tableau 217
3.5 TheTaiwanElectronicCommunications(TEC)
Problem 115 5.4 ImprovingtheSolution 218
ProblemFormulation 116 5.5 CalculatingtheNextTableau 222
ComputerSolutionandInterpretation 117 InterpretingtheResultsofanIteration 224
Summary 121 MovingTowardaBetterSolution 225
WorkedExample 121 InterpretingtheOptimalSolution 228
Problems 123 SummaryoftheSimplexMethod 228
CaseProblem1ProductMix 134 5.6 TableauForm:TheGeneralCase 230
CaseProblem2InvestmentStrategy 135 Greater-Than-or-Equal-toConstraints(‡) 230
CaseProblem3TruckLeasingStrategy 136 EqualityConstraints 234
EliminatingNegativeRight-HandSide
4 Linear Programming Values 235
SummaryoftheStepstoCreateTableau
Applications
137
Form 236
4.1 TheProcessofProblemFormulation 138 5.7 SolvingaMinimizationProblem 237
4.2 ProductionManagementApplications 140 5.8 SpecialCases 239
Make-or-BuyDecisions 140 Infeasibility 239
ProductionScheduling 143 UnboundedProblems 240
WorkforceAssignment 150 AlternativeOptimalSolutions 242
4.3 Blending,DietandFeed-MixProblems 156 Degeneracy 243
4.4 MarketingandMediaApplications 163 Summary 244
MediaSelection 163 WorkedExample 245
MarketingResearch 166 Problems 248
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CONTENTS vii
6 Simplex-Based Sensitivity CaseProblem1DistributionSystemDesign 336
Appendix7.1 ExcelSolutionofTransportation,
Analysis and Duality
254
AssignmentandTransshipmentProblems 338
6.1 SensitivityAnalysiswiththeSimplex
Tableau 255
8 Network Models
ObjectiveFunctionCoefficients 255 344
Right-HandSideValues 258
8.1 Shortest-RouteProblem 345
SimultaneousChanges 265
AShortest-RouteAlgorithm 346
6.2 Duality 266
8.2 MinimalSpanningTreeProblem 354
InterpretationoftheDualVariables 268
AMinimalSpanningTreeAlgorithm 355
UsingtheDualtoIdentifythePrimalSolution 270
8.3 MaximalFlowProblem 357
FindingtheDualofAnyPrimalProblem 270
Summary 362
Summary 272
WorkedExample 362
WorkedExample 273
Problems 363
Problems 274
CaseProblem AmbulanceRouting 368
7 Transportation, Assignment
9 Project Scheduling:
and Transshipment Problems
279 PERT/CPM
370
7.1 TransportationProblem:ANetworkModeland
9.1 ProjectSchedulingWithKnownActivity
aLinearProgrammingFormulation 280
Times 372
ProblemVariations 283
TheConceptofaCriticalPath 373
AGeneralLinearProgrammingModelofthe
DeterminingtheCriticalPath 374
TransportationProblem 285
ContributionsofPERT/CPM 378
7.2 TransportationSimplexMethod:ASpecial- SummaryofthePERT/CPMCriticalPath
PurposeSolutionProcedure 286 Procedure 379
PhaseI:FindinganInitialFeasibleSolution 288 GanttCharts 380
PhaseII:IteratingtotheOptimalSolution 291
9.2 ProjectSchedulingWithUncertainActivity
SummaryoftheTransportationSimplex
Times 381
Method 300
TheDaughertyPorta-VacProject 382
ProblemVariations 302
UncertainActivityTimes 382
7.3 AssignmentProblem:TheNetworkModeland TheCriticalPath 385
aLinearProgrammingFormulation 303 VariabilityinProjectCompletionTime 386
ProblemVariations 305
9.3 ConsideringTime–CostTrade-Offs 388
AGeneralLinearProgrammingModelofthe
CrashingActivityTimes 389
AssignmentProblem 306
Summary 392
MultipleAssignments 307
WorkedExample 392
7.4 AssignmentProblem:ASpecial-Purpose
Problems 394
SolutionProcedure 307
CaseProblem R.C.Coleman 401
FindingtheMinimumNumberofLines 311
Appendix9.1 ActivityonArrowNetworks 402
ProblemVariations 311
7.5 TransshipmentProblem:TheNetworkModel
10 Inventory Models
andaLinearProgrammingFormulation 314 405
ProblemVariations 319
10.1 PrinciplesofInventoryManagement 406
AGeneralLinearProgrammingModelofthe
TheRoleofInventory 406
TransshipmentProblem 320
InventoryCosts 407
7.6 AProductionandInventoryApplication 320
10.2 EconomicOrderQuantity
Summary 324 (EOQ)Model 408
WorkedExample 325 TheHow-Much-to-OrderDecision 411
Problems 327 TheWhen-to-OrderDecision 413
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viii CONTENTS
SensitivityAnalysisfortheEOQModel 414 11.4 SomeGeneralRelationshipsforQueuing
ExcelSolutionoftheEOQModel 415 Models 466
SummaryoftheEOQModelAssumptions 415 11.5 EconomicAnalysisofQueues 468
10.3 EconomicProductionLotSizeModel 416 11.6 OtherQueuingModels 470
TotalCostModel 418
11.7 Single-ChannelQueuingModelwith
EconomicProductionLotSize 420
PoissonArrivalsandArbitraryService
10.4 InventoryModelwithPlannedShortages 421 Times 471
10.5 QuantityDiscountsfortheEOQModel 425 OperatingCharacteristicsfortheM/G/1
Model 471
10.6 Single-PeriodInventoryModelwith
ConstantServiceTimes 472
ProbabilisticDemand 427
JulianoShoeCompany 428 11.8 Multiple-Channel Model with Poisson
ArabianCarRental 431 Arrivals, Arbitrary Service Times and No
Queue 473
10.7 Order-Quantity,ReorderPointModelwith
OperatingCharacteristicsfortheM/G/k
ProbabilisticDemand 433
ModelwithBlockedCustomers
TheHow-Much-to-OrderDecision 434
Cleared 473
TheWhen-to-OrderDecision 435
11.9 QueuingModelswithFiniteCalling
10.8 PeriodicReviewModelwithProbabilistic
Demand 437 Populations 476
OperatingCharacteristicsfortheM/M/1Model
MoreComplexPeriodicReviewModels 440
withaFiniteCallingPopulation 476
Summary 441
WorkedExample 442 Summary 479
Problems 443 WorkedExample 479
Problems 481
CaseProblem1WagnerFabricatingCompany 447
CaseProblem2RiverCityFireDepartment 448 CaseProblem1RegionalAirlines 486
Appendix10.1 DevelopmentoftheOptimalOrder CaseProblem2OfficeEquipment,Inc 487
Quantity(Q)FormulafortheEOQModel 449
Appendix10.2 Development of the Optimal Lot Size 12 Simulation
489
(Q*) Formula for the Production Lot Size
Model 450 12.1 RiskAnalysis 492
PortaComProject 492
What-IfAnalysis 492
11 Queuing Models
451
Simulation 493
SimulationofthePortaComProblem 501
11.1 StructureofaQueuingSystem 452
Single-ChannelQueue 454 12.2 InventorySimulation 504
DistributionofArrivals 454 SimulationoftheButlerInventory
DistributionofServiceTimes 455 Problem 507
Steady-StateOperation 456
12.3 QueuingSimulation 509
11.2 Single-ChannelQueuingModelwithPoisson HongKongSavingsBankATMQueuing
ArrivalsandExponentialServiceTimes 456 System 510
OperatingCharacteristics 457 CustomerArrivalTimes 510
OperatingCharacteristicsfortheDome CustomerServiceTimes 511
Problem 458 SimulationModel 511
Managers’UseofQueuingModels 458 SimulationoftheATMProblem 515
ImprovingtheQueuingOperation 459 SimulationwithTwoATMs 516
ExcelSolutionoftheQueuingModel 461 SimulationResultswithTwoATMs 518
11.3 Multiple-ChannelQueuingModelwithPoisson 12.4 OtherSimulationIssues 520
ArrivalsandExponentialServiceTimes 462 ComputerImplementation 520
OperatingCharacteristics 462 VerificationandValidation 521
OperatingCharacteristicsfortheDome AdvantagesandDisadvantagesofUsing
Problem 464 Simulation 522
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