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E-raamat: Multi-objective Group Decision Making: Methods Software And Applications With Fuzzy Set Techniques (With Cd-rom)

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(Belgian Nuclear Research Centre (Sck.cen) & Ghent Univ, Belgium), (Univ Of Technology Sydney, Australia), (Univ Of Technology Sydney, Australia), (Univ Of Technology Sydney, Australia)
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This book proposes a set of models to describe fuzzy multi-objective decision making (MODM), fuzzy multi-criteria decision making (MCDM), fuzzy group decision making (GDM) and fuzzy multi-objective group decision-making problems, respectively. It also gives a set of related methods (including algorithms) to solve these problems. One distinguishing feature of this book is that it provides two decision support systems software for readers to apply these proposed methods. A set of real-world applications and some new directions in this area are then described to further instruct readers how to use these methods and software in their practice.
Foreword v
Preface vii
Part I: Decision Making, Decision Support Systems, and Fuzzy Sets 1
1. Decision Making
3
1.1 Decision and Decision Makers
3
1.2 Decision Making Process
5
1.3 Problem Modelling and Optimisation
10
1.4 Computerised Decision Support
13
2. Multi-Objective and Multi-Attribute Decision Making
17
2.1 Criteria, Objectives, and Attributes
17
2.2 MODM Models
19
2.3 MODM Methods
21
2.3.1 Classifications
21
2.3.2 Weighting method
25
2.3.3 Goal programming
25
2.3.4 A case-based example
28
2.4 MADM Models
29
2.5 MADM Methods
31
2.5.1 TOPSIS
32
2.5.2 AHP
34
2.5.3 A case-based example
35
2.6 Summary
37
3. Group Decision Making
39
3.1 Decision Groups
39
3.2 Characteristics
40
3.3 Models
42
3.4 Process
44
3.5 Methods
46
3.6 Group Support Systems and Groupware
49
3.7 Summary
51
4. Decision Support Systems
53
4.1 Concepts
53
4.2 Characteristics
55
4.3 Types
56
4.4 Multi-Objective DSS
59
4.5 Multi-Attribute DSS
63
4.6 Group DSS
65
4.7 Intelligent DSS
67
4.8 Web-Based DSS
70
4.9 Components
73
4.10 Summary
75
5. Fuzzy Sets and Systems
77
5.1 Fuzzy Sets
77
5.1.1 Definitions
77
5.1.2 Operations and properties
79
5.1.3 Decomposition theorem and the extension principle
80
5.2 Fuzzy Relations
81
5.3 Fuzzy Numbers
83
5.4 Linguistic Variables
87
5.5 Fuzzy Linear Programming
89
5.5.1 Zimmermann's model
90
5.5.2 Fuzzy parameters
91
5.6 Summary
91
Part II: Fuzzy Multi-Objective Decision Making 93
6. Fuzzy MODM Models
95
6.1 A Problem
95
6.2 Fuzzy Parameter-Based MOLP Models
97
6.2.1 A general FMOLP model
97
6.2.2 An FMOLP, model
100
6.3 Solution Transformation Theories
102
6.3.1 General MOLP transformation
102
6.3.2 Weighted MOLP transformation
111
6.3.3 Constrained MOLP transformation
114
6.3.4 Weighted maximum MOLP transformation
116
6.4 Fuzzy Multi-Objective Linear Goal Programming Models
119
6.5 Summary
121
7. Fuzzy MODM Methods
123
7.1 Related Issues
123
7.2 Fuzzy MOLP
126
7.2.1 Method description
126
7.2.2 A numeral example
130
7.3 Fuzzy MOLGP
136
7.3.1 Method description
137
7.3.2 A numeral example
141
7.4 Interactive FMOLP
146
7.4.1 Method description
146
7.4.2 A numeral example
152
7.5 Summary
159
8. Fuzzy Multi-Objective DSS
161
8.1 System Configuration
161
8.2 System Interface
163
8.3 A Model-Base and Model Management
164
8.4 A Method-Base and Solution Process
167
8.4.1 Fuzzy MOLP
167
8.4.2 Fuzzy MOLGP
167
8.4.3 Interactive FMOLP
170
8.5 Case-Based Examples
173
8.6 Summary
185
Part III: Fuzzy Group Decision Making 187
9. Fuzzy MCDM
189
9.1 A Problem
189
9.2 Models
193
9.3 Fuzzy TOPSIS
194
9.4 Fuzzy AHP
196
9.5 A Hybrid Method
197
9.6 Case-Based Examples
200
9.7 Summary
206
10. Fuzzy Group Decision Making
207
10.1 The Rational-Political Model
207
10.2 Uncertain Factors
210
10.3 An Intelligent FMCGDM Method
212
10.4 A Case-Based Example
217
10.5 Summary
226
11. A Web-Based Fuzzy Group DSS
229
11.1 System Features
229
11.2 System Configuration
231
11.3 System Working Process
233
11.4 Case-Based Examples
235
11.5 Summary
246
Part IV: Fuzzy Multi-Objective Group Decision Making 247
12. Multi-Objective Group DSS
249
12.1 Frameworks
249
12.2 Multi-Objective Based Aggregation Methods
252
12.2.1 Average solution method
252
12.2.2 Weighting objective method
255
12.2.3 Weighting member method
258
12.2.4 Ideal solution method
260
12.2.5 Solution analysis method
262
12.3 An Intelligent MOGDSS
263
12.4 Design of the Intelligent Guide Subsystem
265
12.4.1 Knowledge acquisition process
265
12.4.2 Characteristics analysis models
266
12.4.3 Novice and intermediate modes
267
12.4.4 Logical connectivity and characteristics
268
12.4.5 Questions and responses
269
12.4.6 Inference process
270
12.5 Implementation
272
12.5.1 The MODM method subsystem
272
12.5.2 The intelligent guide subsystem
274
12.5.3 The group subsystem
277
12.6 Summary
279
13. Fuzzy Multi-Objective Group DSS
281
13.1 A Decision Method
281
13.2 System Configuration
285
13.3 System Interface
286
13.4 A Case-Based Example
288
13.5 Summary
298
Part V: Applications 299
14. Environmental Economic Load Dispatch
301
14.1 The Problem
301
14.2 A Fuzzy Dynamic Model
302
14.3 A Transformation Method
303
14.4 A Solution Technique
305
14.5 A Case Study
307
14.6 Summary
312
15. Team Situation Awareness
313
15.1 Situation Awareness
313
15.2 Uncertainty, Inconsistency, and Distributed Environment
314
15.3 A Case-Based Example
316
15.4 Summary
322
16. Reverse Logistics Management
323
16.1 Reverse Logistics Chain
323
16.2 Characteristics of Decision Making in the Reverse Logistics
325
16.3 A Multi-Stage Multi-Criteria Decision Support Model
329
16.4 A Case Study
331
16.5 Summary
339
Appendix A User Manual on FMODSS 341
Appendix B User Manual on FGDSS 355
Bibliography 361
Abbreviation 385
Index 387


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