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New Methods and Applications in Multiple Attribute Decision Making (MADM)
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New Methods and Applications in Multiple Attribute Decision Making (MADM)
von: Alireza Alinezhad, Javad Khalili
Springer-Verlag, 2019
ISBN: 9783030150099
236 Seiten, Download: 5879 KB
 
Format:  PDF
geeignet für: Apple iPad, Android Tablet PC's Online-Lesen PC, MAC, Laptop

Typ: B (paralleler Zugriff)

 

 
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Inhaltsverzeichnis

  Contents 6  
  Preface 14  
  About the Authors 16  
  Introduction 17  
  1 SMART Method 23  
     1.1 Introduction 23  
     1.2 Description of SMART Method 24  
        1.2.1 Rating the Attributes 24  
        1.2.2 The Effective Weights of Alternatives 24  
        1.2.3 The Normalized Weights 25  
        1.2.4 The Final Ranking of Alternatives 25  
     1.3 Case Study 26  
     1.4 Conclusion 28  
  2 REGIME Method 30  
     2.1 Introduction 30  
     2.2 Description of REGIME Method 31  
        2.2.1 Superiority Index 31  
        2.2.2 Superiority Identifier 31  
        2.2.3 Impacts Matrix 31  
        2.2.4 REGIME Matrix 31  
        2.2.5 The Guide Index 32  
        2.2.6 The Final Ranking of Alternatives 32  
     2.3 Case Study 32  
     2.4 Conclusion 35  
  3 ORESTE Method 37  
     3.1 Introduction 37  
     3.2 Description of ORESTE Method 38  
        3.2.1 The Position Matrix 38  
        3.2.2 The Block Distance 38  
        3.2.3 The Block Distance Matrix 38  
        3.2.4 The Final Ranking of Alternatives 38  
     3.3 Case Study 39  
     3.4 Conclusion 41  
  4 VIKOR Method 42  
     4.1 Introduction 42  
     4.2 Description of LP-Metric 43  
     4.3 Description of VIKOR Method 43  
        4.3.1 The {\varvec f}^{*} and {\varvec f}^{ - } Indexes 43  
        4.3.2 The {\varvec S}_{ } and {\varvec R}_{ } Indexes 44  
        4.3.3 The VIKOR Index 44  
        4.3.4 The Final Ranking of Alternatives 44  
     4.4 Case Study 44  
     4.5 Conclusion 46  
  5 PROMETHEE I-II-III Methods 47  
     5.1 Introduction 47  
     5.2 Description of PROMETHEE Methods 48  
        5.2.1 The Preference Function 48  
        5.2.2 The Preference Index 50  
        5.2.3 The Leaving and Entering Flows 50  
        5.2.4 The Net Flow 50  
        5.2.5 Final Ranking of Alternatives (PROMETHEE I Method) 51  
        5.2.6 Final Ranking of Alternatives (PROMETHEE II Method) 51  
        5.2.7 Final Ranking of Alternatives (PROMETHEE III Method) 52  
     5.3 Case Study 52  
     5.4 Conclusion 56  
  6 QUALIFLEX Method 58  
     6.1 Introduction 58  
     6.2 Description of QUALIFLEX Method 59  
        6.2.1 The Initial Permutation of Alternatives 59  
        6.2.2 The Initial Ranking of Alternatives 59  
        6.2.3 The Dominant and Dominated Values 59  
        6.2.4 The Permutation Values of Attributes 60  
        6.2.5 The Permutation Values of Alternatives 60  
        6.2.6 The Final Ranking of Alternatives 60  
     6.3 Case Study 60  
     6.4 Conclusion 63  
  7 SIR Method 64  
     7.1 Introduction 64  
     7.2 Description of SIR Method 65  
        7.2.1 Comparing the Alternatives 65  
        7.2.2 The Preference Function 65  
        7.2.3 The (S) and (I) Indexes and (S) and (I) Matrices 67  
        7.2.4 The Flow Matrix 68  
        7.2.5 The (n) and (r) Flows 68  
        7.2.6 Final Ranking of Alternatives (SIR-SAW Method) 69  
        7.2.7 Final Ranking of Alternatives (SIR-PROMETHEE I Method) 69  
        7.2.8 Final Ranking of Alternatives (SIR-PROMETHEE II Method) 69  
     7.3 Case Study 69  
     7.4 Conclusion 75  
  8 EVAMIX Method 76  
     8.1 Introduction 76  
     8.2 Description of EVAMIX Method 77  
        8.2.1 The Superiority Rate of Alternatives 77  
           8.2.1.1 The First Technique for Calculating Weights 77  
           8.2.1.2 The Second Technique for Calculating Weights 77  
        8.2.2 The Differential Matrix in the Ordinal Attributes 78  
        8.2.3 The Differential Matrix in the Cardinal Attributes 78  
        8.2.4 The Total Dominance 78  
        8.2.5 The Final Ranking of Alternatives 79  
     8.3 Case Study 79  
     8.4 Conclusion 82  
  9 ARAS Method 83  
     9.1 Introduction 83  
     9.2 Description of ARAS Method 84  
        9.2.1 The Normalized Decision Matrix 84  
        9.2.2 The Weighted Normalized Decision Matrix 84  
        9.2.3 The Optimality Function 84  
        9.2.4 The Utility Degree 85  
        9.2.5 The Final Ranking of Alternatives 85  
     9.3 Case Study 85  
     9.4 Conclusion 87  
  10 Taxonomy Method 88  
     10.1 Introduction 88  
     10.2 Description of Taxonomy Method 89  
        10.2.1 The Mean and Standard Deviation of Attributes 89  
        10.2.2 The Standard Matrix 89  
        10.2.3 The Composite Distance Matrix 89  
        10.2.4 Homogenizing the Alternatives 90  
        10.2.5 The Development Pattern 91  
        10.2.6 The Final Ranking of Alternatives 91  
     10.3 Case Study 91  
     10.4 Conclusion 94  
  11 MOORA Method 95  
     11.1 Introduction 95  
     11.2 Description of MOORA Method 96  
        11.2.1 The Normalized Decision Matrix 96  
        11.2.2 The Reference Points 96  
        11.2.3 The Assessment Values 96  
        11.2.4 The Final Ranking of Alternatives 96  
     11.3 Case Study 97  
     11.4 Conclusion 99  
  12 COPRAS Method 100  
     12.1 Introduction 100  
     12.2 Description of COPRAS Method 101  
        12.2.1 The Normalized Decision Matrix 101  
        12.2.2 The Weighted Normalized Decision Matrix 101  
        12.2.3 The Maximizing and Minimizing Indexes 101  
        12.2.4 The Relative Significance Value 102  
        12.2.5 The Final Ranking of Alternatives 102  
     12.3 Case Study 102  
     12.4 Conclusion 104  
  13 WASPAS Method 105  
     13.1 Introduction 105  
     13.2 Description of WASPAS Method 106  
        13.2.1 The Normalized Decision Matrix 106  
        13.2.2 The Additive Relative Importance 106  
        13.2.3 The Multiplicative Relative Importance 106  
        13.2.4 The Joint Generalized Criterion (Q) 107  
        13.2.5 The Final Ranking of Alternatives 107  
     13.3 Case Study 107  
     13.4 Conclusion 110  
  14 SWARA Method 111  
     14.1 Introduction 111  
     14.2 Description of SWARA Method 111  
        14.2.1 The Initial Prioritization of Attributes 111  
        14.2.2 The Coefficient (K) 112  
        14.2.3 The Initial Weight 112  
        14.2.4 The Relative Weight 112  
        14.2.5 The Final Ranking of Attributes 112  
     14.3 Case Study 112  
     14.4 Conclusion 114  
  15 DEMATEL Method 115  
     15.1 Introduction 115  
     15.2 Description of DEMATEL Method 116  
        15.2.1 The Normalized Direct Relation Matrix 116  
        15.2.2 The Total Relation Matrix 116  
        15.2.3 The Cause and Effect Values 116  
        15.2.4 The Threshold Value (a) 117  
        15.2.5 The Interrelationship Map 117  
        15.2.6 The Final Ranking of Attributes 117  
     15.3 Case Study 118  
     15.4 Conclusion 120  
  16 MACBETH Method 121  
     16.1 Introduction 121  
     16.2 Description of MACBETH Method 122  
        16.2.1 Converting of Semantic Scale into Numerical Scale 122  
        16.2.2 The Reference Levels 122  
        16.2.3 The MACBETH Score (V) 122  
        16.2.4 The Overall Score 123  
        16.2.5 The Final Ranking of Alternatives 123  
     16.3 Case Study 123  
     16.4 Conclusion 125  
  17 ANP Method 127  
     17.1 Introduction 127  
     17.2 Description of ANP Method 128  
        17.2.1 The Priority Vectors 128  
        17.2.2 The Super Matrix 129  
        17.2.3 The Cluster Matrix 129  
        17.2.4 The Weighted Super Matrix 129  
        17.2.5 The Limit Super Matrix 129  
        17.2.6 The Utility Index 130  
        17.2.7 The Final Ranking of Alternatives 130  
     17.3 Case Study 130  
     17.4 Conclusion 136  
  18 MAUT Method 138  
     18.1 Introduction 138  
     18.2 Description of MAUT Method 139  
        18.2.1 The Normalized Decision Matrix 139  
        18.2.2 The Marginal Utility Score 139  
        18.2.3 The Final Utility Score 139  
        18.2.4 The Final Ranking of Alternatives 140  
     18.3 Case Study 140  
     18.4 Conclusion 142  
  19 IDOCRIW Method 143  
     19.1 Introduction 143  
     19.2 Description of IDOCRIW Method 144  
        19.2.1 The Normalized Decision Matrix 144  
        19.2.2 The Degree of Entropy 144  
        19.2.3 The Entropy Weight (W) 144  
        19.2.4 The Square Matrix 144  
        19.2.5 The Relative Impact Loss Matrix 145  
        19.2.6 The Weight System Matrix 145  
        19.2.7 The Criterion Impact Loss Weight (Q) 146  
        19.2.8 The Aggregate Weight (?) 146  
        19.2.9 The Final Ranking of Attributes 146  
     19.3 Case Study 146  
     19.4 Conclusion 150  
  20 TODIM Method 152  
     20.1 Introduction 152  
     20.2 Description of TODIM Method 153  
        20.2.1 The Normalized Decision Matrix 153  
        20.2.2 The Relative Weight 153  
        20.2.3 The Dominance Degree 153  
        20.2.4 The Overall Dominance Degree 154  
        20.2.5 The Final Ranking of Alternatives 154  
     20.3 Case Study 154  
     20.4 Conclusion 157  
  21 EDAS Method 158  
     21.1 Introduction 158  
     21.2 Description of EDAS Method 159  
        21.2.1 The Average Solution 159  
        21.2.2 The Positive and Negative Distances from Average Solution 159  
        21.2.3 The Weighted PDA and NDA 159  
        21.2.4 Weighted Normalized PDA and NDA 160  
        21.2.5 The Appraisal Score 160  
        21.2.6 The Final Ranking of Alternatives 160  
     21.3 Case Study 160  
     21.4 Conclusion 164  
  22 PAMSSEM I & II 165  
     22.1 Introduction 165  
     22.2 Description of PAMSSEM Methods 166  
        22.2.1 The Local Outranking Index 166  
        22.2.2 The Concordance Index 166  
        22.2.3 The Local Discordance Index 167  
        22.2.4 The Outranking Degree 167  
        22.2.5 The Entering and Leaving Flows 168  
        22.2.6 The Net Flow 168  
        22.2.7 The Final Ranking of Alternatives (PAMSSEM I Method) 168  
        22.2.8 The Final Ranking of Alternatives (PAMSSEM II Method) 168  
     22.3 Case Study 169  
     22.4 Conclusion 172  
  23 ELECTRE I–II–III Methods 174  
     23.1 Introduction 174  
     23.2 Description of ELECTRE Methods 175  
        23.2.1 The Normalized Decision Matrix 175  
        23.2.2 The Weighted Normalized Decision Matrix 175  
        23.2.3 The Dominant Matrix 175  
        23.2.4 The Dominated Matrix 175  
        23.2.5 The Concordance Matrix 176  
        23.2.6 The Discordance Matrix 176  
        23.2.7 The Aggregate Dominant Matrix 177  
        23.2.8 The Final Ranking of Alternatives (ELECTRE I Method) 177  
        23.2.9 The Final Ranking of Alternatives (ELECTRE II Method) 177  
        23.2.10 The Final Ranking of Alternatives (ELECTRE III Method) 178  
     23.3 Case Study 179  
     23.4 Conclusion 186  
  24 EXPROM I & II Method 188  
     24.1 Introduction 188  
     24.2 Description of EXPROM Methods 189  
        24.2.1 The Weak Preference Function 189  
        24.2.2 The Weak Preference Index 189  
        24.2.3 The Strict Preference Function 191  
        24.2.4 The Strict Preference Index 192  
        24.2.5 The Entering and Leaving Flows 192  
        24.2.6 The Net Flow 192  
        24.2.7 The Final Ranking of Alternatives (EXPROM I Method) 193  
        24.2.8 The Final Ranking of Alternatives (EXPROM II Method) 193  
     24.3 Case Study 194  
     24.4 Conclusion 198  
  25 MABAC Method 199  
     25.1 Introduction 199  
     25.2 Description of MABAC Method 200  
        25.2.1 The Normalized Decision Matrix 200  
        25.2.2 The Weighted Normalized Decision Matrix 200  
        25.2.3 The Border Approximation Area Matrix 200  
        25.2.4 The Distance from the Border Approximation Area 201  
        25.2.5 The Total Distances from the Border Approximate Area 201  
        25.2.6 The Final Ranking of Alternatives 201  
     25.3 Case Study 201  
     25.4 Conclusion 203  
  26 CRITIC Method 205  
     26.1 Introduction 205  
     26.2 Description of CRITIC Method 206  
        26.2.1 The Normalized Decision Matrix 206  
        26.2.2 The Correlation Coefficient 206  
        26.2.3 The Index (C) 206  
        26.2.4 The Weight of Attributes 207  
        26.2.5 The Final Ranking of Attributes 207  
     26.3 Case Study 207  
     26.4 Conclusion 209  
  27 KEMIRA Method 210  
     27.1 Introduction 210  
     27.2 Description of KEMIRA Method 211  
        27.2.1 The Normalized Decision Matrix 211  
        27.2.2 The Median Matrix 211  
        27.2.3 The Set of Attribute Weights 212  
        27.2.4 The Final Weight of Attributes 212  
        27.2.5 The Final Value of Alternatives 212  
        27.2.6 The Final Ranking of Alternatives 213  
     27.3 Case Study 213  
     27.4 Conclusion 220  
  References 221  
  Index 234  


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