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Multi-criteria Decision Analysis

Methods and Software
 E-Book
Sofort lieferbar | Lieferzeit:3-5 Tage I
ISBN-13:
9781118644911
Einband:
E-Book
Seiten:
312
Autor:
Alessio Ishizaka
eBook Typ:
Adobe Digital Editions
eBook Format:
E-Book
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

Inhaltsangabe

Foreword xi

Acknowledgements xiii

1 General introduction 1

1.1 Introduction 1

1.2 Decision problems 3

1.3 MCDA methods 4

1.4 MCDA software 5

1.5 Selection of MCDA methods 5

1.6 Outline of the book 8

References 9

Part I FULL AGGREGATION APPROACH 11

2 Analytic hierarchy process 13

2.1 Introduction 13

2.2 Essential concepts of AHP 13

2.2.1 Problem structuring 14

2.2.2 Priority calculation 16

2.2.3 Consistency check 18

2.2.4 Sensitivity analysis 19

2.3 AHP software: MakeItRational 20

2.3.1 Problem structuring 20

2.3.2 Preferences and priority calculation 21

2.3.3 Consistency check 22

2.3.4 Results 24

2.3.5 Sensitivity analysis 25

2.4 In the black box of AHP 27

2.4.1 Problem structuring 27

2.4.2 Judgement scales 28

2.4.3 Consistency 31

2.4.4 Priorities derivation 33

2.4.5 Aggregation 39

2.5 Extensions of AHP 40

2.5.1 Analytic hierarchy process ordering 41

2.5.2 Group analytic hierarchy process 44

2.5.3 Clusters and pivots for a large number of alternatives 48

2.5.4 AHPSort 50

References 54

3 Analytic network process 59

3.1 Introduction 59

3.2 Essential concepts of ANP 59

3.2.1 Inner dependency in the criteria cluster 60

3.2.2 Inner dependency in the alternative cluster 63

3.2.3 Outer dependency 64

3.2.4 Influence matrix 67

3.3 ANP software: Super Decisions 68

3.3.1 Problem structuring 69

3.3.2 Assessment of pairwise comparison 70

3.3.3 Results 73

3.3.4 Sensitivity analysis 74

3.4 In the black box of ANP 76

3.4.1 Markov chain 76

3.4.2 Supermatrix 78

References 80

4 Multi-attribute utility theory 81

4.1 Introduction 81

4.2 Essential concepts of MAUT 81

4.2.1 The additive model 83

4.3 RightChoice 89

4.3.1 Data input and utility functions 89

4.3.2 Results 93

4.3.3 Sensitivity analysis 94

4.3.4 Group decision and multi-scenario analysis 95

4.4 In the black box of MAUT 97

4.5 Extensions of the MAUT method 98

4.5.1 The UTA method 98

4.5.2 UTAGMS 105

4.5.3 GRIP 111

References 112

5 MACBETH 114

5.1 Introduction 114

5.2 Essential concepts of MACBETH 114

5.2.1 Problem structuring: Value tree 115

5.2.2 Score calculation 117

5.2.3 Incompatibility check 118

5.3 Software description: M-MACBETH 122

5.3.1 Problem structuring: Value tree 122

5.3.2 Evaluations and scores 122

5.3.3 Incompatibility check 125

5.3.4 Results 127

5.3.5 Sensitivity analysis 127

5.3.6 Robustness analysis 127

5.4 In the black box of MACBETH 131

5.4.1 LP-MACBETH 131

5.4.2 Discussion 133

References 133

Part II OUTRA Extensions of PROMETHEE 170

6.5.1 PROMETHEE GDSS 170

6.5.2 FlowSort: A sorting or supervised classification method 172

References 177

7 ELECTRE 180

7.1 Introduction 180

7.2 Essentials of the ELECTRE methods 180

7.2.1 ELECTRE III 183

7.3 The Electre III-IV software 189

7.3.1 Data entry 190

7.3.2 Entering preference parameters 191

7.3.3 Results 193

7.4 In the black box of ELECTRE III 194

7.4.1 Outranking relations 194

7.4.2 Partial concordance degree 195

7.4.3 Global concordance degree 196

7.4.4 Partial discordance degree 196

7.4.5 Outranking degree 197

7.4.6 Partial ranking: Exploitation of the outranking relations 199

7.4.7 Some properties 203

7.5 ELECTRE-Tri 204

7.5.1 Introduction 204

7.5.2 Preference relations 205

7.5.3 Assignment rules 207

7.5.4 Properties 207

References 210

Part III GOAL, ASPIRATION OR REFERENCE-LEVEL APPROACH 213

8 TOPSIS 215

8.1 Introduction 215

8.2 Essentials of TOPSIS 215

References 221

9 Goal programming 222

9.1 Introduction 222

9.2 Essential concepts of goal programming 222

9.3 Software description 227

9.3.1 Microsoft Excel Solver 227

9.4 Extensions of the goal programming 228

9.4.1 Weighted goal programming 228

9.4.2 Lexicographic goal programming 230

9.4.3 Chebyshev goal programming 232

References 234

10 Data Envelopment Analysis 235
Jean-Marc Huguenin

10.1 Introduction 235

10.2 Essential concepts of DEA 236

10.2.1 An efficiency measurement method 236

10.2.2 A DEA case study 237

10.2.3 Multiple outputs and inputs 247

10.2.4 Types of efficiency 248

10.2.5 Managerial implications 249

10.3 The DEA software 252

10.3.1 Building a spreadsheet in Win4DEAP 254

10.3.2 Running a DEA model 255

10.3.3 Interpreting results 257

10.4 In the black box of DEA 262

10.4.1 Constant returns to scale 263

10.4.2 Variable returns to scale 266

10.5 Extensions of DEA 268

10.5.1 Adjusting for the environment 268

10.5.2 Preferences 268

10.5.3 Sensitivity analysis 269

10.5.4 Time series data 270

References 270

Part IV INTEGRATED SYSTEMS 275

11 Multi-method platforms 277

11.1 Introduction 277

11.2 Decision Deck 278

11.3 DECERNS 278

11.3.1 The GIS module 279

11.3.2 The MCDA module 281

11.3.3 The GDSS module 284

11.3.4 Integration 286

References 287

Appendix: Linear optimization 288

A.1 Problem modelling 288

A.2 Graphical solution 289

A.3 Solution with Microsoft Excel 289

Index 293

Foreword xi
Acknowledgements xiii

1 General introduction 1

1.1 Introduction 1

1.2 Decision problems 3

1.3 MCDA methods 4

1.4 MCDA software 5

1.5 Selection of MCDA methods 5

1.6 Outline of the book 8

References 9

Part I FULL AGGREGATION APPROACH 11

2 Analytic hierarchy process 13

2.1 Introduction 13

2.2 Essential concepts of AHP 13

2.3 AHP software: MakeItRational 20

2.4 In the black box of AHP 27

2.5 Extensions of AHP 40

References 54

3 Analytic network process 59

3.1 Introduction 59

3.2 Essential concepts of ANP 59

3.3 ANP software: Super Decisions 68

3.4 In the black box of ANP 76

References 80

4 Multi-attribute utility theory 81

4.1 Introduction 81

4.2 Essential concepts of MAUT 81

4.3 RightChoice 89

4.4 In the black box of MAUT 97

4.5 Extensions of the MAUT method 98

References 112

5 MACBETH 114

5.1 Introduction 114

5.2 Essential concepts of MACBETH 114

5.3 Software description: M-MACBETH 122

5.4 In the black box of MACBETH 131

References 133

Part II OUTRANKING APPROACH 135

6 PROMETHEE 137

6.1 Introduction 137

6.2 Essential concepts of the PROMETHEE method 137

6.3 The Smart Picker Pro software 149

6.4 In the black box of PROMETHEE 160

6.5 Extensions of PROMETHEE 170

References 177

7 ELECTRE 180

7.1 Introduction 180

7.2 Essentials of the ELECTRE methods 180

7.3 The Electre III-IV software 189

7.4 In the black box of ELECTRE III 194

7.5 ELECTRE-Tri 204

References 210

Part III GOAL, ASPIRATION OR REFERENCE-LEVEL APPROACH 213

8 TOPSIS 215

8.1 Introduction 215

8.2 Essentials of TOPSIS 215

References 221

9 Goal programming 222

9.1 Introduction 222

9.2 Essential concepts of goal programming 222

9.3 Software description 227

9.4 Extensions of the goal programming 228

References 234

10 Data Envelopment Analysis 235
Jean-Marc Huguenin

10.1 Introduction 235

10.2 Essential concepts of DEA 236

10.3 The DEA software 252

10.4 In the black box of DEA 262

10.5 Extensions of DEA 268

References 270

Part IV INTEGRATED SYSTEMS 275

11 Multi-method platforms 277

11.1 Introduction 277

11.2 Decision Deck 278

11.3 DECERNS 278

References 287

Appendix: Linear optimization 288

A.1 Problem modelling 288

A.2 Graphical solution 289

A.3 Solution with Microsoft Excel 289

Index 293

This book presents an introduction to MCDA followed by more detailed chapters about each of the leading methods used in this field. Comparison of methods and software is also featured to enable readers to choose the most appropriate method needed in their research.

Worked examples as well as the software featured in the book are available on an accompanying website.

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