كتاب Production Planning in Production Networks

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Production Planning in Production Networks
Models for Medium and Short-term Planning
Pierluigi Argoneto, Giovanni Perrone,
Paolo Renna, Giovanna Lo Nigro,
Manfredi Bruccoleri, Sergio Noto La Diega

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Contents
1 Introduction and Literature Overview .1
1.1 Introduction 1
1.2 Production Planning in High-tech, High-volume Industry .2
1.3 Strategic and Tactical Level .2
1.4 Operational Models: Optimization and Decision Support 5
1.4.1 Mathematical Approach 7
1.4.2 Queuing and Stochastic Approaches .8
1.4.3 Heuristics and Simulation-based Approaches .8
1.5 Motivation 9
1.6 Book Outline 10
1.7 References 10
2 Game Theory: an Overview .13
2.1 Introduction 13
2.2 Game Setup 14
2.3 Non-cooperative Static Games .15
2.4 Existence of Equilibrium 16
2.5 Multiple Equilibria .17
2.6 Dynamic Games .17
2.7 Simultaneous Moves: Repeated and Stochastic Games .18
2.8 Cooperative Games 18
2.9 N-Person Cooperative Games 19
2.10 Characteristic Function and Imputation .20
2.11 Shapley Value 21
2.12 The Bargaining Game Model .22
2.13 References 23
3 Negotiation: an Overview .25
3.1 Introduction 25
3.2 Negotiation and Rational Self-interested Agents .28
3.3 Negotiation Models 29viii Contents
3.4 Underlying Principle for Electronic Negotiation 30
3.5 Electronic Negotiation Protocols 31
3.6 Characteristics that Differentiate Negotiations Protocols .31
3.7 Modelling Approaches and Solution Concepts 32
3.7.1 Decision Theory 33
3.7.2 Game Theory .34
3.7.3 Negotiation Analysis .34
3.8 Strategic Negotiation 35
3.9 Negotiation Strategies 35
3.10 References 36
4 Multiple-agent Systems: an Overview .41
4.1 Introduction 41
4.2 Applications .42
4.3 Challenging Issues 43
4.4 Individual Agent Reasoning .44
4.5 Observable Worlds .45
4.6 Stochastic Transitions and Utilities 45
4.7 Distributed Decision Making .47
4.8 Recognising and Resolving Conflicts .48
4.9 Communicating Agents 48
4.10 References 49
5 Distributed Production Planning in Reconfigurable Production
Networks .51
5.1 Introduction 51
5.2 Production Planning in DPS .52
5.2.1 Context of the Semiconductor Industry .52
5.2.2 PP in the Considered Industrial Case 54
5.2.3 IDEF0 Architecture .55
5.2.4 Agent Architecture 55
5.3 Top PP Level 57
5.4 High PP Level 57
5.5 Medium PP Level .58
5.6 Low PP Level .58
5.7 Shop-floor PP Level .59
5.8 References 60
6 Distributed Models for Planning Capacity of Reconfigurable Production
Networks at Medium Term 63
6.1 Introduction 63
6.2 Initial State .63
6.3 The Centralised Model .64
6.4 The Negotiation Model 65
6.5 The Game-theoretical Model 66
6.5.1 Case 1: Characteristic Function hij > 0 .67
6.5.2 Case 2: Characteristic Function hij < 0 .67Contents ix
6.5.3 The Bargaining Solution 70
6.6 Simulation Case Study .71
6.6.1 The Simulation Environment .71
6.6.2 Simulation Case Study 74
6.7 Results 74
6.7.1 Two-way Analysis of Variance .75
6.7.2 Design of Experiment (DoE) .88
6.8 References .95
7 Distributed Models for Plant Capacity Allocation .97
7.1 Introduction 97
7.2 Initial State .97
7.3 The Centralised Model .98
7.4 The Negotiation Model 99
7.4.1 Generative Function 99
7.4.2 Reactive Function 99
7.5 The Game -theoretical Model .100
7.6 The Simulation .101
7.6.1 The Simulation Environment .101
7.6.2 The Simulation Case Study .104
7.7 Results 105
7.7.1 Efficiency Performance Analysis: Two-way ANOVA .105
7.7.2 Efficiency Performance Analysis: DoE .115
7.7.3 Distance Performance Analysis: Two-way ANOVA 121
7.7.4 Distance Performance Analysis: DoE .130
7.7.5 Number of Reconfigurations Performance Analysis: Two-way
ANOVA .136
7.7.6 Number of Reconfigurations Performance Analysis: DoE 147
7.7.7 Absolute Residual Performance Analysis: Two-way ANOVA .153
7.7.8 Absolute Residual Performance Analysis: DoE 164
8 Distributed Production Planning Models: an Integrated Approach 171
8.1 Introduction 171
8.2 The Simulation Case Study 172
8.3 Results 173
8.3.1 Efficiency Performance Analysis: Two-way ANOVA .173
8.3.2 Efficiency Performance Analysis: DoE .182
8.3.3 Distance Performance Analysis: Two-way ANOVA 192
8.3.4 Distance Performance Analysis: DoE 200
8.3.5 Absolute Residual Performance Analysis: Two-ways ANOVA .209
8.3.6 Absolute Residual Performance Analysis: DoE 214
8.4 Conclusions 223
9 Conclusions 225
9.1 Summary 225
9.2 Major Scientific Contributions of This Book .226
9.3 Directions for Future Work 227x Contents
Appendix A: Simulation Results Related to Chapter 6 .229
Appendix B: Simulation Input Parameters and Results
Related to Chapter 7 233
Appendix C: Simulation Input Parameters and Results
Related to Chapter 8 247
Index .

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