Multi-criteria decision analysis : methods and software

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.

Author Notes

Alessio Ishizaka
Reader in Decision Analysis, Portsmouth Business School, University of Portsmouth, UK

Philippe Nemery
Senior Research Scientist, SAP Labs - China, Shanghai, PRC

Jean-Marc Huguenin

Foreword	p. xi
Acknowledgements	p. xiii
1 General introduction	p. 1
1.1 Introduction	p. 1
1.2 Decision problems	p. 3
1.3 MCDA methods	p. 4
1.4 MCDA software	p. 5
1.5 Selection of MCDA methods	p. 5
1.6 Outline of the book	p. 8
References	p. 9
Part I Full Aggregation Approach	p. 11
2 Analytic hierarchy process	p. 13
2.1 Introduction	p. 13
2.2 Essential concepts of AHP	p. 13
2.2.1 Problem structuring	p. 14
2.2.2 Priority calculation	p. 16
2.2.3 Consistency check	p. 18
2.2.4 Sensitivity analysis	p. 19
2.3 AHP software: MakeItRational	p. 20
2.3.1 Problem structuring	p. 20
2.3.2 Preferences and priority calculation	p. 21
2.3.3 Consistency check	p. 22
2.3.4 Results	p. 24
2.3.5 Sensitivity analysis	p. 25
2.4 In the black box of AHP	p. 27
2.4.1 Problem structuring	p. 27
2.4.2 Judgement scales	p. 28
2.4.3 Consistency	p. 31
2.4.4 Priorities derivation	p. 33
2.4.5 Aggregation	p. 39
2.5 Extensions of AHP	p. 40
2.5.1 Analytic hierarchy process ordering	p. 41
2.5.2 Group analytic hierarchy process	p. 44
2.5.3 Clusters and pivots for a large number of alternatives	p. 48
2.5.4 AHPSort	p. 50
References	p. 54
3 Analytic network process	p. 59
3.1 Introduction	p. 59
3.2 Essential concepts of ANP	p. 59
3.2.1 Inner dependency in the criteria cluster	p. 60
3.2.2 Inner dependency in the alternative cluster	p. 63
3.2.3 Outer dependency	p. 64
3.2.4 Influence matrix	p. 67
3.3 ANP software: Super Decisions	p. 68
3.3.1 Problem structuring	p. 69
3.3.2 Assessment of pairwise comparison	p. 70
3.3.3 Results	p. 73
3.3.4 Sensitivity analysis	p. 74
3.4 In the black box of ANP	p. 76
3.4.1 Markov chain	p. 76
3.4.2 Supermatrix	p. 78
References	p. 80
4 Multi-attribute utility theory	p. 81
4.1 Introduction	p. 81
4.2 Essential concepts of MAUT	p. 81
4.2.1 The additive model	p. 83
4.3 Right Choice	p. 89
4.3.1 Data input and utility functions	p. 89
4.3.2 Results	p. 93
4.3.3 Sensitivity analysis	p. 94
4.3.4 Group decision and multi-scenario analysis	p. 95
4.4 In the black box of MAUT	p. 97
4.5 Extensions of the MAUT method	p. 98
4.5.1 The UTA method	p. 98
4.5.2 UTA GMS	p. 105
4.5.3 GRIP	p. 111
References	p. 112
5 MACBETH	p. 114
5.1 Introduction	p. 114
5.2 Essential concepts of MACBETH	p. 114
5.2.1 Problem structuring: Value tree	p. 115
5.2.2 Score calculation	p. 117
5.2.3 Incompatibility check	p. 118
5.3 Software description: M-MACBETH	p. 122
5.3.1 Problem structuring: Value tree	p. 122
5.3.2 Evaluations and scores	p. 122
5.3.3 Incompatibility check	p. 125
5.3.4 Results	p. 127
5.3.5 Sensitivity analysis	p. 127
5.3.6 Robustness analysis	p. 127
5.4 In the black box of MACBETH	p. 131
5.4.1 LP-MACBETH	p. 131
5.4.2 Discussion	p. 133
References	p. 133
Part II Outranking Approach	p. 135
6 Promethee	p. 137
6.1 Introduction	p. 137
6.2 Essential concepts of the PROMETHEE method	p. 137
6.2.1 Unicriterion preference degrees	p. 138
6.2.2 Unicriterion positive, negative and net flows	p. 142
6.2.3 Global flows	p. 143
6.2.4 The Gaia plane	p. 146
6.2.5 Sensitivity analysis	p. 148
6.3 The Smart Picker Pro software	p. 149
6.3.1 Data entry	p. 149
6.3.2 Entering preference parameters	p. 151
6.3.3 Weights	p. 153
6.3.4 PROMETHEE II ranking	p. 155
6.3.5 Gaia plane	p. 151
6.3.6 Sensitivity analysis	p. 158
6.4 In the black box of PROMETHEE	p. 160
6.4.1 Unicriterion preference degrees	p. 162
6.4.2 Global preference degree	p. 163
6.4.3 Global flows	p. 164
6.4.4 PROMETHEE I and PROMETHEE II ranking	p. 166
6.4.5 The Gaia plane	p. 167
6.4.6 Influence of pairwise comparisons	p. 168
6.5 Extensions of PROMETHEE	p. 170
6.5.1 PROMETHEE GDSS	p. 170
6.5.2 FlowSort: A sorting or supervised classification method	p. 172
References	p. 177
7 ELECTRE	p. 180
7.1 Introduction	p. 180
7.2 Essentials of the ELECTEE methods	p. 180
7.2.1 ELECTRE III	p. 183
7.3 The Electre III-IV software	p. 189
7.3.1 Data entry	p. 190
7.3.2 Entering preference parameters	p. 191
7.3.3 Results	p. 193
7.4 In the black box of ELECTRE III	p. 194
7.4.1 Outranking relations	p. 194
7.4.2 Partial concordance degree	p. 195
7.4.3 Global concordance degree	p. 196
7.4.4 Partial discordance degree	p. 196
7.4.5 Outranking degree	p. 197
7.4.6 Partial ranking: Exploitation of the outranking relations	p. 199
7.4.7 Some properties	p. 203
7.5 ELECTRE-Tri	p. 204
7.5.1 Introduction	p. 204
7.5.2 Preference relations	p. 205
7.5.3 Assignment rules	p. 207
7.5.4 Properties	p. 207
References	p. 210
Part III Goal, Aspiration or Reference-Level Approach	p. 213
8 TOPSIS	p. 215
8.1 Introduction	p. 215
8.2 Essentials of TOPSIS	p. 215
References	p. 221
9 Goal programming	p. 222
9.1 Introduction	p. 222
9.2 Essential concepts of goal programming	p. 222
9.3 Software description	p. 227
9.3.1 Microsoft Excel Solver	p. 227
9.4 Extensions of the goal programming	p. 228
9.4.1 Weighted goal programming	p. 228
9.4.2 Lexicographic goal programming	p. 230
9.4.3 Chebyshev goal programming	p. 232
References	p. 234
10 Data Envelopment Analysis	p. 235
10.1 Introduction	p. 235
10.2 Essential concepts of DEA	p. 236
10.2.1 An efficiency measurement method	p. 236
10.2.2 A DEA case study	p. 237
10.2.3 Multiple outputs and inputs	p. 247
10.2.4 Types of efficiency	p. 248
10.2.5 Managerial implications	p. 249
10.3 The DEA software	p. 252
10.3.1 Building a spreadsheet in Win4DEAP	p. 254
10.3.2 Running a DEA model	p. 255
10.3.3 Interpreting results	p. 257
10.4 In the black box of DEA	p. 262
10.4.1 Constant returns to scale	p. 263
10.4.2 Variable returns to scale	p. 266
10.5 Extensions of DEA	p. 268
10.5.1 Adjusting for the environment	p. 268
10.5.2 Preferences	p. 268
10.5.3 Sensitivity analysis	p. 269
10.5.4 Time series data	p. 270
References	p. 270
Part IV Integrated Systems	p. 275
11 Multi-method platforms	p. 277
11.1 Introduction	p. 277
11.2 Decision Deck	p. 278
11.3 DECERNS	p. 278
11.3.1 The GIS module	p. 279
11.3.2 The MCDA module	p. 281
11.3.3 The GDSS module	p. 284
11.3.4 Integration	p. 286
References	p. 287
Appendix: Linear optimization	p. 288
A.1 Problem modelling	p. 288
A.2 Graphical solution	p. 289
A.3 Solution with Microsoft Excel	p. 289
Index	p. 293

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