Multi-criteria Decision Analysis: Methods and Software

299 Pages·2013·5.977 MB·English

by  Alessio Ishizaka, Philippe Nemery

Multi-Criteria Decision Analysis
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Multi-Criteria Decision Analysis
Methods and Software
Alessio Ishizaka
ReaderinDecisionAnalysis,PortsmouthBusinessSchool
UniversityofPortsmouth,UK
Philippe Nemery
SeniorResearchScientist, SAPLabs–China, Shanghai, PRC
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Thiseditionfirstpublished2013
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LibraryofCongressCataloging-in-PublicationData
Ishizaka,Alessio.
Multi-criteriadecisionanalysis:methodsandsoftware/AlessioIshizaka,PhilippeNemery.
pagescm
Includesbibliographicalreferencesandindex.
ISBN978-1-119-97407-9(cloth)
1.Multiplecriteriadecisionmaking. 2.Multiplecriteriadecisionmaking–Dataprocessing.
3.Decisionsupportsystems. I.Nemery,Philippe. II.Title.
T57.95.I842013
003(cid:3).56–dc23
2013004490
AcataloguerecordforthisbookisavailablefromtheBritishLibrary.
ISBN:978-1-119-97407-9
Typesetin10/12ptTimesbyAptaraInc.,NewDelhi,India
1 2013
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Contents
Foreword xi
Acknowledgements xiii
1 Generalintroduction 1
1.1 Introduction 1
1.2 Decisionproblems 3
1.3 MCDAmethods 4
1.4 MCDAsoftware 5
1.5 SelectionofMCDAmethods 5
1.6 Outlineofthebook 8
References 9
PartI FULLAGGREGATIONAPPROACH 11
2 Analytichierarchyprocess 13
2.1 Introduction 13
2.2 EssentialconceptsofAHP 13
2.2.1 Problemstructuring 14
2.2.2 Prioritycalculation 16
2.2.3 Consistencycheck 18
2.2.4 Sensitivityanalysis 19
2.3 AHPsoftware:MakeItRational 20
2.3.1 Problemstructuring 20
2.3.2 Preferencesandprioritycalculation 21
2.3.3 Consistencycheck 22
2.3.4 Results 24
2.3.5 Sensitivityanalysis 25
2.4 IntheblackboxofAHP 27
2.4.1 Problemstructuring 27
2.4.2 Judgementscales 28
2.4.3 Consistency 31
2.4.4 Prioritiesderivation 33
2.4.5 Aggregation 39
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vi CONTENTS
2.5 ExtensionsofAHP 40
2.5.1 Analytichierarchyprocessordering 41
2.5.2 Groupanalytichierarchyprocess 44
2.5.3 Clustersandpivotsforalargenumberofalternatives 48
2.5.4 AHPSort 50
References 54
3 Analyticnetworkprocess 59
3.1 Introduction 59
3.2 EssentialconceptsofANP 59
3.2.1 Innerdependencyinthecriteriacluster 60
3.2.2 Innerdependencyinthealternativecluster 63
3.2.3 Outerdependency 64
3.2.4 Influencematrix 67
3.3 ANPsoftware:SuperDecisions 68
3.3.1 Problemstructuring 69
3.3.2 Assessmentofpairwisecomparison 70
3.3.3 Results 73
3.3.4 Sensitivityanalysis 74
3.4 IntheblackboxofANP 76
3.4.1 Markovchain 76
3.4.2 Supermatrix 78
References 80
4 Multi-attributeutilitytheory 81
4.1 Introduction 81
4.2 EssentialconceptsofMAUT 81
4.2.1 Theadditivemodel 83
4.3 RightChoice 89
4.3.1 Datainputandutilityfunctions 89
4.3.2 Results 93
4.3.3 Sensitivityanalysis 94
4.3.4 Groupdecisionandmulti-scenarioanalysis 95
4.4 IntheblackboxofMAUT 97
4.5 ExtensionsoftheMAUTmethod 98
4.5.1 TheUTAmethod 98
4.5.2 UTAGMS 105
4.5.3 GRIP 111
References 112
5 MACBETH 114
5.1 Introduction 114
5.2 EssentialconceptsofMACBETH 114
5.2.1 Problemstructuring:Valuetree 115
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CONTENTS vii
5.2.2 Scorecalculation 117
5.2.3 Incompatibilitycheck 118
5.3 Softwaredescription:M-MACBETH 122
5.3.1 Problemstructuring:Valuetree 122
5.3.2 Evaluationsandscores 122
5.3.3 Incompatibilitycheck 125
5.3.4 Results 127
5.3.5 Sensitivityanalysis 127
5.3.6 Robustnessanalysis 127
5.4 IntheblackboxofMACBETH 131
5.4.1 LP-MACBETH 131
5.4.2 Discussion 133
References 133
PartII OUTRANKINGAPPROACH 135
6 PROMETHEE 137
6.1 Introduction 137
6.2 EssentialconceptsofthePROMETHEEmethod 137
6.2.1 Unicriterionpreferencedegrees 138
6.2.2 Unicriterionpositive,negativeandnetflows 142
6.2.3 Globalflows 143
6.2.4 TheGaiaplane 146
6.2.5 Sensitivityanalysis 148
6.3 TheSmartPickerProsoftware 149
6.3.1 Dataentry 149
6.3.2 Enteringpreferenceparameters 151
6.3.3 Weights 153
6.3.4 PROMETHEEIIranking 155
6.3.5 Gaiaplane 157
6.3.6 Sensitivityanalysis 158
6.4 IntheblackboxofPROMETHEE 160
6.4.1 Unicriterionpreferencedegrees 162
6.4.2 Globalpreferencedegree 163
6.4.3 Globalflows 164
6.4.4 PROMETHEEIandPROMETHEEIIranking 166
6.4.5 TheGaiaplane 167
6.4.6 Influenceofpairwisecomparisons 168
6.5 ExtensionsofPROMETHEE 170
6.5.1 PROMETHEEGDSS 170
6.5.2 FlowSort:Asortingorsupervisedclassificationmethod 172
References 177
7 ELECTRE 180
7.1 Introduction 180
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viii CONTENTS
7.2 EssentialsoftheELECTREmethods 180
7.2.1 ELECTREIII 183
7.3 TheElectreIII-IVsoftware 189
7.3.1 Dataentry 190
7.3.2 Enteringpreferenceparameters 191
7.3.3 Results 193
7.4 IntheblackboxofELECTREIII 194
7.4.1 Outrankingrelations 194
7.4.2 Partialconcordancedegree 195
7.4.3 Globalconcordancedegree 196
7.4.4 Partialdiscordancedegree 196
7.4.5 Outrankingdegree 197
7.4.6 Partialranking:Exploitationoftheoutrankingrelations 199
7.4.7 Someproperties 203
7.5 ELECTRE-Tri 204
7.5.1 Introduction 204
7.5.2 Preferencerelations 205
7.5.3 Assignmentrules 207
7.5.4 Properties 207
References 210
PartIII GOAL,ASPIRATIONORREFERENCE-LEVEL
APPROACH 213
8 TOPSIS 215
8.1 Introduction 215
8.2 EssentialsofTOPSIS 215
References 221
9 Goalprogramming 222
9.1 Introduction 222
9.2 Essentialconceptsofgoalprogramming 222
9.3 Softwaredescription 227
9.3.1 MicrosoftExcelSolver 227
9.4 Extensionsofthegoalprogramming 228
9.4.1 Weightedgoalprogramming 228
9.4.2 Lexicographicgoalprogramming 230
9.4.3 Chebyshevgoalprogramming 232
References 234
10 DataEnvelopmentAnalysis 235
Jean-MarcHuguenin
10.1 Introduction 235
10.2 EssentialconceptsofDEA 236
10.2.1 Anefficiencymeasurementmethod 236
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CONTENTS ix
10.2.2 ADEAcasestudy 237
10.2.3 Multipleoutputsandinputs 247
10.2.4 Typesofefficiency 248
10.2.5 Managerialimplications 249
10.3 TheDEAsoftware 252
10.3.1 BuildingaspreadsheetinWin4DEAP 254
10.3.2 RunningaDEAmodel 255
10.3.3 Interpretingresults 257
10.4 IntheblackboxofDEA 262
10.4.1 Constantreturnstoscale 263
10.4.2 Variablereturnstoscale 266
10.5 ExtensionsofDEA 268
10.5.1 Adjustingfortheenvironment 268
10.5.2 Preferences 268
10.5.3 Sensitivityanalysis 269
10.5.4 Timeseriesdata 270
References 270
PartIV INTEGRATEDSYSTEMS 275
11 Multi-methodplatforms 277
11.1 Introduction 277
11.2 DecisionDeck 278
11.3 DECERNS 278
11.3.1 TheGISmodule 279
11.3.2 TheMCDAmodule 281
11.3.3 TheGDSSmodule 284
11.3.4 Integration 286
References 287
Appendix:Linearoptimization 288
A.1 Problemmodelling 288
A.2 Graphicalsolution 289
A.3 SolutionwithMicrosoftExcel 289
Index 293
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Foreword
Thegrowingrecognitionthatdecisionmakerswilloftentrytoachievemultiple,and
usuallyconflicting,objectiveshasledduringthelastthreedecadestothedevelopment
ofmulti-criteriadecisionanalysis(MCDA).Thisisnowavastfieldofresearch,with
itsscientificcommunityanditsspecializedjournals,aswellasalargeandgrowing
number of real-world applications, for supporting both public policy making and
decisionsbyprivatecorporations.
Studentsandpractitionerscomingtothefield,however,willbesurprisedbythe
plethora of alternative methods, overloaded by the array of software available, and
puzzled by the diversity of approaches that an analyst needs to choose from. For
precisely these reasons, this book is a very welcome event for the field. Alessio
IshizakaandPhilippeNemeryhavemanagedtoprovideanaccessible,butrigorous,
introductiontothemainexistingMCDAmethodsavailableintheliterature.
There are several features of the book that are particularly innovative. First, it
providesabalancedassessmentofeachmethod,andpositionsthemintermsofthe
typeofevaluationthatthedecisionrequires(asinglechoiceamongalternatives,the
rankingofallalternatives,thesortingofalternativesintocategories,orthedescription
ofconsequences)andthelevelofpreferenceinformationthateachmethodrequires
(from utility functions to no preference information). This taxonomy helps both
researchers and practitioners in locating adequate methods for the problems they
needtoanalyze.
Second,themethodsarepresentedwiththerightlevelofformulationandaxiom-
atizationforanintroductorycourse.Thismakesthebookaccessibletoanyonewith
abasicquantitativebackground.Readerswhowishtolearningreaterdepthabouta
particularmethodcanenjoythemoreadvancedcontentcovered‘intheblackbox’of
eachchapter.
Third,thebookillustrateseachmethodwithwidelyavailableandfreesoftware.
Thishastwomajorbenefits.Readerscaneasilyseehowthemethodworksinpractice
via an example, consolidating the knowledge and the theoretical content. They can
also reflect on how the method could be used in practice, to facilitate real-world
decision-makingprocesses.
Fourth,instructorsusingthebook,aswellasreaders,canbenefitfromthecom-
panion website (www.wiley.com/go/multi criteria decision analysis) and
theavailabilityofsoftwarefilesandanswerstoexercises.
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xii FOREWORD
This book should therefore be useful reading for anyone who wants to learn
moreaboutMCDA,orforthoseMCDAresearcherswhowanttolearnmoreabout
otherMCDAmethodsandhowtousespecializedsoftwaretosupportmulti-criteria
decisionmaking.
GilbertoMontibeller
DepartmentofManagement
LondonSchoolofEconomics
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