Multicriteria Methodology for Decision Aidingaxiomatic results should be at the heart of such a science. Through them, we should be able to enlighten and scientifically assist decision-making processes especially by: - making that wh ich is objective stand out more c1early from that which is less objective; - separating robust from fragile conc1usions; - dissipating certain forms of misunderstanding in communication; - avoiding the pitfall of illusory reasoning; - emphasizing, once they are understood, incontrovertible results. The difficulties I encountered at the begining of my career as an operations researcher, and later as a consultant, made me realize that there were some limitations on objectivity in decision-aiding. In my opinion, five major aspects must be taken into consideration: 1) The borderline (or frontier) between what is and what is not feasible is often fuzzy. Moreover, this borderline is frequently modified in light of what is found from the study itself. 2) In many real-world problems, the "decision maker D" does not really exist as a person truly able to make adecision. Usually, several people (actors or stakeholders) take part in the decision process, and it is important not to confuse the one who ratifies adecision with the so-called decision maker in the decision ai ding process. This decision maker is in fact the person or the set of persons for whom or in the name of whom decision aiding effort is provided. |
Contents
Decision Problems and Processes | 3 |
Decision Aiding Major and the Rold of Models | 7 |
212 Limiting the scope of the model | 8 |
213 The family of questions | 9 |
22 Decision Aiding | 10 |
222 Aiding for whom? | 11 |
223 Aiding by whom? | 12 |
224 Presence of a client | 13 |
812 Elementary consequences | 130 |
8122 Illustrations and practical considerations | 132 |
8132 Types of scales and practical considerations | 134 |
814 State indicators and consequence spectrum | 135 |
815 Examples | 137 |
82 Evaluating an Action Dispersion Indicators to Model Imprecision Uncertainty and Inaccurate Determination | 144 |
821 Lack of knowledge and state indicator deficiencies | 145 |
822 Dispersion thresholds | 148 |
225 Aid and neutrality | 14 |
226 Aid and Objectivity | 15 |
Reference Examples | 19 |
32 National or Regional Development Problems | 21 |
33 Advertising Problems | 23 |
34 Research and Development Problems | 24 |
35 Operations Problems | 25 |
36 Selection Problems | 28 |
37 Manufacturing Problems | 29 |
Phases and Options of an Approach to Decision Aiding General Ideas of the Methodology | 31 |
412 Study phase and decision process development state | 33 |
42 The Proposed Methodology | 34 |
Analyzing consequences and developing criteria | 35 |
Modeling comprehensive preferences and operationally aggregating performances | 36 |
425 Comments | 37 |
HOW TO DETERMINE WHAT IS POSSIBLE AND IN WHAT TERMS TO FORMULATE A PROBLEM | 39 |
Actions and Decision Aiding | 41 |
identification problems | 44 |
52 The Set of Potential Actions | 47 |
522 Examples | 49 |
Problematics as Guides in Decision Aiding | 57 |
Help choose a best action or develop a selection procedure | 58 |
Help sort actions according to norms or build an assignment procedure | 62 |
613 Ranking problematic Pš¾ Help rank actions in order of decreasing preference or build an ordering procedure | 64 |
Help describe actions and their consequences in a formalized and systematic manner or develop a cognitive procedure | 68 |
62 Remarks on Choosing the Problematic | 69 |
622 Examples | 70 |
623 Multiple cases | 73 |
HOW TO DETERMINE PREFERENCES AND ON WHAT BASES | 75 |
Preference Indifference Incomparability Binary Relations and Basic Structures | 79 |
Basic Concepts | 81 |
7112 Basic situations and the axiom of limited comparability | 84 |
System of preference relations | 86 |
7122 Systems of preference relations and the axiom of limited comparability | 88 |
7123 Comments on incomparability and weak preference | 91 |
713 Consolidated situations and associated binary relations | 92 |
Perfect system of preference relations | 93 |
7133 Jpreference Kpreference basic system of outranking relations | 95 |
7134 Links among these and other relations | 97 |
72 Principal Structures and Functional Relations | 98 |
721 Graphical representations and an example system of preference relations | 99 |
b Notation for systems of preference relations | 100 |
The mayors preferences | 101 |
722 Basic structures of SPRs that exclude or obscure incomparability | 105 |
b Complete orders and intransitive tournaments | 106 |
b2 Functional representation of a complete order | 107 |
a first look at complete basic systems of outranking relations BSOR | 108 |
a2 Functional representation | 109 |
b Structure of a semiorder | 111 |
b2 Semiorder properties | 112 |
b3 Definition and functional representation | 114 |
c1 Comparison of intervalactions | 115 |
c2 Definitions and special cases | 116 |
b Pseudoorder structure | 117 |
b2 Definition and nonfunctional representations | 118 |
b3 Functional representation | 119 |
c Directed semiorder structure | 120 |
c2 Similarities with semiorders and functional representation | 121 |
723 Basic structures of SPRs with incomparability | 122 |
7233 Other R T V structures | 123 |
724 Comparing preference differences or exchanges | 124 |
b Preference relations on A x A | 126 |
COMPARING ACTIONS AND MODELING CONSEQUENCES SUMMARY | 127 |
81 Consequences of an Action Dimensions and Associated State Indicators | 128 |
8222 Dispersion thresholds and indicators | 150 |
8223 Properties of intrinsic dispersion thresholds | 151 |
823 Modulated dispersion indicators or modulation indicators | 152 |
8231 Dispersion factors determined from subjective opinions allowing distinctions in state importance or likelihood | 153 |
8232 Dispersion factors determined from objective observations allowing qualitative modulation of state importance or likelihood | 155 |
8233 Dispersion factors represented by distributions of nonrandom magnitudes allowing quantitative modulation of state importance or likelihood | 157 |
824 Referenced dispersion indicator | 158 |
Principles of clarity universality and reliability | 160 |
Comparing Action and Developing Criteria | 163 |
91 The Concept of Criterion | 164 |
912 Definition and comments | 167 |
92 Constructing Criteria from Consequences | 170 |
922 Criteria with one dimension and a nonpoint state indicator | 172 |
9221 Point reduction on the dimension | 173 |
a2 Basic remarks and a first look at utility theory | 174 |
b Point reduction based on percentiles or on other dispersion characteristics | 176 |
another look at utility theory | 177 |
9222 Splitting dimension i | 178 |
923 Criterion function based on a subset of dimensions | 180 |
a One dimension is dominant among the I dimensions | 181 |
b I consists of two or three dimensions whose scales can be reduced to a few degrees | 182 |
93 True Criteria SemiCriteria PreCriteria PseudoCriteria | 184 |
932 Indifference and preference thresholds | 188 |
933 Pseudocriteria semicriteria precriteria | 191 |
934 Determining indifference and preference thresholds | 193 |
b Case where gs support is a point indicator with thresholds | 194 |
941 Comparing preference differences along a criterions significance axis | 195 |
942 Gradation and gradable criteria | 199 |
Preference difference commensurability along a criterions significance axis | 202 |
944 Von NeumannMorgenstern expected utility criteria and preference difference commensurability based on lottery comparisons | 205 |
9442 Expected utility as a measure | 209 |
HOW TO PROCEED FROM MULTIPLE CRITERIA TO COMPREHENSIVE PREFERENCES AND DEVELOP RECOMMENDATIONS | 211 |
Coherent Criterion Family and Decision Aiding in the Description Problematic | 215 |
101 Coherent Criterion Family | 216 |
102 Performance Tableau | 220 |
Problem of Criteria Dependence | 223 |
1032 Structural or statistical dependence among criteria components | 225 |
Links between significance axis preferences and exterior consequences | 227 |
104 Motivation for multiple criteria | 230 |
1041 Dominance | 231 |
1042 Rates of substitution | 232 |
1043 Concordance | 233 |
1044 Discordance and veto | 234 |
Modeling Comprehensive Preferences Three Operational Approaches for Progressing beyond the Description Problematic | 237 |
111 Operational Approach and the Aggregation Problem | 238 |
1112 Operational approach and options | 239 |
Use of a Single Synthesizing Criterion without Incomparabilities | 241 |
1122 Typical aggregation functions | 244 |
1123 Important comments | 246 |
Systhesis by Outranking with Incomparablilities | 247 |
1132 Typical outranking tests | 250 |
1133 Important comments | 262 |
Interactive Local Judgments with TrialandError Iterations | 263 |
1142 Typical interaction protocols | 264 |
1143 Important comments | 265 |
Specific Difficulties in Choke Sorting and Ranking Problematics | 269 |
122 Problems with NonIndependent Actions | 271 |
123 Problems with Multiple Scenarios | 273 |
124 Problems with Conflicting Value Systems | 274 |
125 Problems with Strategic Hesitations | 275 |
126 Problems with Poorly Defined Sets of Actions and HardtoEstimate Performance Levels | 276 |
Bibliography | 277 |
289 | |
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Common terms and phrases
aā aā actors affine transformation aggregation aggregation problem analyst application associated assume asymmetric relation axiom basic binary relations Chapter comparing complete preorder comprehensive preferences concept considered continued in Section corresponding cost criterion function criterion g decision aiding decision maker decision process defined definition degrees denote develop dimension discuss dispersion indicator dispersion thresholds elementary consequences elements equivalence classes evaluation example French version function g functional representation illustrate importance inaccurate determination incomparability indifference lead methodology modulation indicator multicriteria multiple criteria objective operational approach Operational Research outranking relation pair of actions performance levels phase possible potential actions preference differences preference model preference relations preference thresholds presented problem problematic procedure pseudo-order ranking represent scale semi-order significance axis situations specific SPR's stakeholders strict preference structure subset symmetric system of preference Table task transitive translator's note UniversitĆ© Paris-Dauphine value system weak preference