Multiple Criteria Decision Making Applications in Environmentally Conscious Manufacturing and Product Recovery

193 Pages·2018·3.544 MB·English

by  Surendra M. Gupta, Mehmet Ali Ilgin

Multiple Criteria
Decision Making
Applications in
Environmentally
Conscious
Manufacturing and
Product Recovery

Multiple Criteria
Decision Making
Applications in
Environmentally
Conscious
Manufacturing and
Product Recovery
By
Surendra M. Gupta and Mehmet Ali Ilgin
CRC Press
Taylor & Francis Group
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To Sharda Gupta, Monica Gupta, and Neil Gupta
– Surendra M. Gupta
Bahar Sarı Ilgı n
– Mehmet Ali Ilgin

Contents
Preface ..................................................................................................................xiii
Acknowledgments ................................................................................................xv
Authors ................................................................................................................xvii
1. Multiple Criteria Decision Making in Environmentally
Conscious Manufacturing and Product Recovery ...................................1
1.1 Introduction ...........................................................................................1
1.2 Quantitative Techniques ......................................................................2
1.2.1 Goal Programming ..................................................................2
1.2.2 Fuzzy Goal Programming ......................................................4
1.2.3 Physical Programming ............................................................5
1.2.3.1 Reverse and Closed-Loop Supply-Chain
Network Design .......................................................5
1.2.3.2 Disassembly-to-Order Systems ..............................6
1.2.4 Data Envelopment Analysis ...................................................7
1.2.5 Other Mathematical Models ..................................................7
1.3 Qualitative Techniques.........................................................................8
1.3.1 Analytical Hierarchy Process .................................................8
1.3.2 Fuzzy Analytical Hierarchy Process .....................................9
1.3.3 Analytical Network Process .................................................10
1.3.4 DEMATEL ...............................................................................10
1.3.5 TOPSIS .....................................................................................11
1.3.6 ELECTRE .................................................................................11
1.3.7 PROMETHEE .........................................................................12
1.3.8 Multiattribute Utility Theory (MAUT) ...............................12
1.3.9 VIKOR ......................................................................................12
1.3.10 MACBETH ..............................................................................13
1.3.11 Case-Based Reasoning ..........................................................13
1.3.12 Gray Relational Analysis ......................................................13
1.3.13 Other Techniques ...................................................................14
1.4 Mixed Techniques ...............................................................................14
1.4.1 Analytical Hierarchy Process and Data Envelopment
Analysis ...................................................................................14
1.4.2 PROMETHEE and Goal Programming ..............................14
1.4.3 PROMETHEE and Analytical Hierarchy Process .............15
1.4.4 PROMETHEE and Analytical Network Process ...............15
1.4.5 Analytical Hierarchy Process and Case-Based
Reasoning ................................................................................15
1.4.6 Analytical Network Process and Goal Programming .....15
vii
viii Contents
1.4.7 Analytical Network Process and Data Envelopment
Analysis ...................................................................................15
1.4.8 Analytical Hierarchy Process and Genetic Algorithms ...16
1.4.9 Analytical Hierarchy Process and Neural Networks .......16
1.4.10 Analytical Hierarchy Process and Analytical
Network Process ....................................................................16
1.4.11 Analytical Hierarchy Process and TOPSIS ........................16
1.4.12 Analytical Network Process and Gray Relational
Analysis ...................................................................................16
1.4.13 Analytical Hierarchy Process and Simulation ..................16
1.4.14 Analytical Hierarchy Process and Structural
Equation Modeling ................................................................17
1.4.15 Approaches Involving More than Two Techniques ..........17
1.5 Heuristics and Metaheuristics ..........................................................18
1.6 Simulation ............................................................................................19
1.7 Conclusions ..........................................................................................20
References .......................................................................................................21
2. Techniques Used in the Book .....................................................................35
2.1 Goal Programming .............................................................................35
2.2 Fuzzy Logic ..........................................................................................36
2.3 Linear Physical Programming ..........................................................39
2.4 Data Envelopment Analysis ..............................................................41
2.4.1 CCR Model ..............................................................................42
2.4.2 BCC Model ..............................................................................43
2.5 Analytical Hierarchy Process ............................................................44
2.6 Analytic Network Process .................................................................45
2.7 DEMATEL ............................................................................................46
2.8 TOPSIS ..................................................................................................48
2.9 ELECTRE ..............................................................................................49
2.10 PROMETHEE .......................................................................................52
2.11 VIKOR ...................................................................................................54
2.12 MACBETH ...........................................................................................56
2.13 Gray Relational Analysis ...................................................................57
2.14 Simulation ............................................................................................59
2.15 Conclusions ..........................................................................................60
References .......................................................................................................60
3. Goal Programming .......................................................................................63
3.1 The Model ............................................................................................63
3.1.1 Revenues .................................................................................63
3.1.1.1 Reuse Revenue ........................................................63
3.1.1.2 Recycle Revenue .....................................................64
3.1.1.3 New Product Sale Revenue ...................................64
3.1.2 Costs .........................................................................................64
Contents ix
3.1.2.1 Collection/Retrieval Cost......................................64
3.1.2.2 Processing Cost .......................................................64
3.1.2.3 Inventory Cost ........................................................65
3.1.2.4 Transportation Cost ...............................................65
3.1.2.5 Disposal Cost ..........................................................65
3.1.3 System Constraints ................................................................66
3.2 Numerical Example ............................................................................68
3.3 Other Models .......................................................................................69
3.4 Conclusions ..........................................................................................70
References .......................................................................................................70
4. Fuzzy Goal Programming ..........................................................................71
4.1 The Model ............................................................................................71
4.1.1 Revenues .................................................................................72
4.1.1.1 Reuse Revenue ........................................................72
4.1.1.2 Recycle Revenue .....................................................73
4.1.1.3 New Product Sale Revenue ...................................73
4.1.2 Costs .........................................................................................73
4.1.2.1 Collection/Retrieval Cost......................................73
4.1.2.2 Processing Cost .......................................................73
4.1.2.3 Inventory Cost ........................................................74
4.1.2.4 Transportation Cost ...............................................74
4.1.2.5 Disposal Cost ..........................................................75
4.1.3 System Constraints ................................................................75
4.2 Numerical Example ............................................................................77
4.3 Other Models .......................................................................................78
4.4 Conclusions ..........................................................................................79
References .......................................................................................................79
5. Linear Physical Programming ...................................................................81
5.1 The Model ............................................................................................81
5.1.1 Model Formulation ................................................................81
5.1.1.1 Class-1S Criteria (Smaller-Is-Better) ....................81
5.1.1.2 Class-1H Criteria ...................................................82
5.1.1.3 Goal Constraints .....................................................82
5.1.1.4 System Constraints.................................................83
5.2 Numerical Example ............................................................................84
5.3 Other Models .......................................................................................85
5.4 Conclusions ..........................................................................................86
References .......................................................................................................87
6. Data Envelopment Analysis .......................................................................89
6.1 The Model ............................................................................................89
6.2 Numerical Example ............................................................................89
6.3 Other Models .......................................................................................91