Preface ........................................................ xi
Biographical Note ............................................ xiii
Chapter 1 Introduction ......................................... 1
1.1 Profile of Multiple Criterion Decision Making .............. 1
1.2 Historical Development of Multiple Attribute Decision
Making ..................................................... 3
1.3 Historical Development of Multiple Objective Decision
Making ..................................................... 6
1.4 Introduction to Fuzzy Sets ................................. 8
1.4.1 Basic Concepts ...................................... 8
1.4.2 Fuzzy Arithmetic Operations ........................ 10
1.4.2.1 Extension Principle ....................... 10
1.4.2.2 α-Cut Arithmetic .......................... 11
1.4.3 Ranking Fuzzy Numbers .............................. 11
1.5 Outline of the Book ....................................... 12
SECTION I Concepts and Theory of Multi-Objective Decision
Making
Chapter 2 Multi-Objective Evolutionary Algorithms ............. 17
2.1 Concepts of Genetic Algorithms ............................ 17
2.2 GA Procedures ............................................. 18
2.2.1 String Representation .............................. 18
2.2.2 Population Initialization .......................... 18
2.2.3 Fitness Computation ................................ 19
2.2.4 Genetic Operators .................................. 19
2.2.4.1 Selection ................................. 19
2.2.4.2 Crossover ................................. 20
2.2.4.3 Mutation .................................. 20
2.3 Multi-Objective Evolutionary Algorithms (MOEAs) ........... 21
2.3.1 Numerical Example .................................. 22
Chapter 3 Goal Programming .................................... 25
3.1 Goal Setting .............................................. 25
3.2 Weighted Goal Programming ................................. 26
3.3 Lexicography Goal Programming ............................. 28
3.4 Min-Max (Tchebycheff) Goal Programming .................... 30
3.5 Fuzzy Goal Programming .................................... 31
Chapter 4 Compromise Solution and TOPSIS ...................... 37
4.1 Compromise Solution ....................................... 37
4.2 TOPSIS for MODM ........................................... 40
4.3 Fuzzy Compromise Solution and TOPSIS ...................... 42
Chapter 5 De Novo Programming and Changeable Parameters ....... 47
5.1 De Novo Programming ....................................... 47
5.2 De Novo Programming by Genetic Algorithms ................. 51
5.3 De Novo Programming by Compromise Solution ................ 52
5.4 Extensions of De Novo Programming ......................... 54
5.5 MOP with Changeable Parameters ............................ 56
Model 5.1: MOP with Changeable Budgets .................... 57
Model 5.2: MOP with Changeable Objective Coefficients ..... 59
Model 5.3: MOP with Changeable Technological
Coefficients .............................................. 60
Chapter 6 Multi-Stage Programming ............................. 65
6.1 Dynamic Programming ....................................... 65
6.2 Application of Multi-Stage Problem: Competence Sets ....... 68
6.3 Fuzzy Multi-Stage Multi-Objective Competence Sets ......... 70
Appendix .................................................. 74
Chapter 7 Multi-Level Multi-Objective Programming ............. 75
7.1 Bi-Level Programming ...................................... 75
7.2 Multiple Level Programming ................................ 77
7.3 Fuzzy Programming for Multi-Level Multi-Objective
Programming ............................................... 78
Chapter 8 Data Envelopment Analysis ........................... 83
8.1 Traditional DEA ........................................... 83
8.2 Network DEA ............................................... 87
8.2.1 Input-Oriented Efficiency .......................... 89
8.2.2 Output-Oriented Efficiency ......................... 90
8.2.3 Non-Oriented Efficiency ............................ 90
8.3 Fuzzy Multi-Objective Programming (FMOP) to DEA ........... 94
8.3.1 Model 1 ............................................ 94
8.3.2 Model 2 ............................................ 96
SECTION II Applications of Multi-Objective Decision Making
Chapter 9 Motivation and Resource Allocation for Strategic
Alliances through the De Novo Perspective ..................... 101
9.1 Motivations for Strategic Alliances ...................... 102
9.1.1 Transaction Cost Theory ........................... 102
9.1.2 Resource-Based View ............................... 103
9.2 Problems of Resource Allocation .......................... 103
9.3 De Novo Perspective of Strategic Alliances ............... 105
9.4 Numerical Example ........................................ 106
9.5 Discussion ............................................... 109
9.6 Conclusions .............................................. 110
Chapter 10 Choosing Best Alliance Partners and Allocating
Optimal Alliance Resources Using Fuzzy Multi-Objective Dummy
Programming Model ............................................. 113
10.1 Review of Strategic Alliances ............................ 114
10.2 Fuzzy Multiple Objective Dummy Programming ............... 116
10.2.1 Joint Venture Model ............................... 118
10.2.2 M&A Model ......................................... 119
10.3 Numerical Example ........................................ 120
10.4 Discussion ............................................... 123
10.5 Conclusions .............................................. 124
Chapter 11 Multiple-Objective Planning for Supply Chain
Production and Distribution Model: Bicycle Manufacturer ....... 125
11.1 Literature on Supply Chain and Multi-Objective
Programming for Production and Distribution .............. 126
11.1.1 Relevant Supply Chain Literature .................. 126
11.1.2 Multi-Objective and Fuzzy Multi-Objective
Programming ....................................... 127
11.1.2.1 Multi-Objective Compromise Programming ... 127
11.1.2.2 Weighted Multi-Objective Programming ..... 128
11.1.2.3 Fuzzy Multi-Objective Programming ........ 129
11.1.2.4 Weighted Fuzzy Multi-Objective
Programming .............................. 129
11.1.2.5 Two-Phase Fuzzy Multi-Objective
Programming .............................. 130
11.2 Establishing Model for Bicycle Supply Chain .............. 130
11.2.1 Basic Assumptions, Definitions, and
Establishment of Model ............................ 130
11.2.2 Model Construction ................................ 131
11.2.2.1 Objective 1: Maximize Total Profit and
Competitiveness 131
11.2.2.2 Objective 2: Maximize Level of Customer
Service Quality per Period ............... 133
11.2.3 Model Constraints ................................. 133
11.2.3.1 Raw Material Constraint .................. 133
11.2.3.2 Productivity Constraint .................. 134
11.2.3.3 Inventory Constraint ..................... 134
11.2.3.4 Relationship of Product Distribution
and Demand ............................... 135
11.2.3.5 Non-Negative Constraint .................. 135
11.3 Real Empirical Case of a Bicycle Manufacturer ............ 135
11.3.1 Problem Description and Definitions ............... 135
11.3.2 Results and Analysis .............................. 136
11.3.3 Sensitivity Analyses and Discussions .............. 139
11.4 Conclusions and Recommendations .......................... 140
Appendix A: Max-Min Operation ................................. 142
A.1 Determination of Ceiling and Bottom Limits of
Objectives and Constraint Equations ................. 142
A.2 Establishment of Membership Function ................ 142
A.3 Setting Membership Function for Decision Making
Set μD(x) ........................................... 142
A.4 Turning Multiple Objectives into Single Objective
for Resolution ...................................... 143
Appendix B: Concept of Weighted Fuzzy Multi-Objective
Programming ................................................... 143
Chapter 12 Fuzzy Interdependent Multi-Objective Programming ... 145
12.1 Interdependence with Objectives .......................... 146
12.2 Fuzzy Interdependent Multi-Objective Programming ......... 148
12.3 Numerical Example ........................................ 155
12.4 Discussion ............................................... 157
12.5 Conclusions .............................................. 158
Appendix ...................................................... 159
Chapter 13 Novel Algorithm for Uncertain Portfolio
Selection ..................................................... 161
13.1 Possibilistic Regression ................................. 162
13.2 Mellin Transformation .................................... 163
13.3 Numerical Example ........................................ 165
13.4 Discussion ............................................... 167
13.5 Conclusions .............................................. 170
Chapter 14 Multi-Objective Optimal Planning for Designing
Relief Delivery Systems ....................................... 171
14.1 Characteristics of Relief Distribution Systems ........... 172
14.2 Relief Distribution Model ................................ 172
14.2.1 Assumptions ....................................... 172
14.2.2 Model Establishment ............................... 173
14.2.3 Symbol Explanation ................................ 174
14.2.3.1 Parameters and Variables ................. 174
14.2.3.2 Variables Used ........................... 174
14.2.4 Distribution Model ................................ 175
14.2.5 Model Modification and Resolution ................. 178
14.3 Relief Distribution Operation: Case Analysis ............. 179
14.3.1 Information Content and Data Collection ........... 179
14.3.2 Pre-Operation Stage ............................... 179
14.3.3 Disaster Information Transmission ................. 181
14.3.4 Route Planning and Network Analysis ............... 182
14.4 Case Illustration and Data Analysis ...................... 183
14.4.1 Case illustration ................................. 183
14.4.2 Data Analysis and Discussion ...................... 184
14.5 Conclusions and Recommendations .......................... 189
Chapter 15 Comparative Productivity Efficiency for Global
Telecoms ...................................................... 191
15.1 Global Telecommunication Trends .......................... 192
15.1.1 Fixed-Mobile Substitution (FMS) ................... 192
15.1.2 Internet Broadband ................................ 193
15.1.2.1 Broadband Access ......................... 193
15.1.2.2 Broadband Penetration .................... 194
15.1.2.3 Convergence of 4C Services ............... 194
15.1.3 Mobile Market ..................................... 194
15.2 Data and Methods ......................................... 195
15.2.1 Data Collection ................................... 195
15.2.2 DEA Methods ....................................... 196
15.2.2.1 Classical Efficiency Measure ............. 196
15.2.2.2 Andersen & Petersen (A&P) Efficiency
Measure .................................. 196
15.2.2.3 Efficiency Achievement Measure ........... 197
15.2.3 DEA Assessment Procedures ......................... 197
15.2.4 Productivity Efficiency Measure ................... 198
15.2.4.1 Descriptive Statistics ................... 198
15.2.4.2 Isotonicity Test ......................... 198
15.2.4.3 Common Weight for Efficiency
Achievement Measure ...................... 198
15.3 Empirical Results and Discussions ........................ 199
15.3.1 Productivity Efficiency ........................... 200
15.3.2 Efficient DMUs .................................... 200
15.3.3 CCR versus EBITDA Margin (%) ...................... 200
15.3.4 Efficiency Ranking Comparison ..................... 202
15.3.5 Efficiency Comparison ............................. 205
15.3.5.1 Regions .................................. 205
15.3.5.2 State-Owned and Privatized Patterns ...... 206
15.3.6 Efficient DMUs .................................... 207
15.3.7 Operating Strategy Case Study ..................... 208
15.4 Conclusions .............................................. 209
Appendix A: Global Broadband Penetration Rankings ............. 210
Appendix B: Global Mobile Penetration Rankings ................ 211
Appendix C: DEA Efficiency Measures ........................... 211
С.1 Classical Efficiency Measure ........................ 211
C.2 A&P Efficiency Measure .............................. 213
C.3 Efficiency Achievement Measure ...................... 214
Appendix D: Reference Websites ................................ 216
Chapter 16 Fuzzy Multiple Objective Programming in Interval
Piecewise Regression Model .................................... 219
16.1 Introduction to Measure of Fitness and Fuzzy Multiple
Objective Programming .................................... 220
16.2 Fuzzy Multiple Objective Programming in Piecewise
Regression Model ......................................... 222
16.3 Numerical Examples ....................................... 225
16.3.1 Example 1 ......................................... 225
16.3.2 Example 2 ......................................... 226
16.4 Conclusions .............................................. 227
Bibliography .................................................. 229
Notes ......................................................... 265
Index ......................................................... 301
|
