Design and Analysis of Simulation Experiments
Buku ini diterbitkan tahun 2008 oleh Springer Science+Business Media, LLC. New York adalah buku Edisi Pertama.
Judul: Design and Analysis of Simulation Experiments
Oleh: Jack P.C. Kleijnen
Penerbit: Springer Science+Business Media, LLC. New York
Tahun: 2008
Jumlah Halaman: 229 hal.
Penulis:
Jack P.C. Kleijnen
Tilburg University
Tilburg, The Netherlands
Lingkup Pembahasan:
Buku ini merupakan penerus dari beberapa buku lain yang saya tulis di (sekitar) topik yang sama. Buku pertama terdiri dari dua volume, dan diterbitkan di 1974/1975 (dan diterjemahkan ke dalam bahasa Rusia pada tahun 1978). Penggantinya diterbitkan pada tahun 1987. Pada tahun 1992, bersama dengan Willem van Groenendaal menulis lebih umum buku tentang simulasi, yang termasuk update dari bagian dari buku saya tahun 1987. Buku ini berfokus pada aspek-aspek Dase.
Daftar Isi:
1 Introduction 1
1.1 What is simulation? 1
1.2 What is DASE? 7
1.3 DASE symbols and terms 10
1.4 Solutions for exercises 12
2 Low-order polynomial regression metamodels and their designs: basics 15
2.1 Introduction 16
2.2 Linear regression analysis: basics 19
2.3 Linear regression analysis: first-order polynomials 27
2.3.1 First-order polynomial with a single factor 27
2.3.2 First-order polynomial with several factors 28
2.4 Designs for first-order polynomials: resolution-III 36
2.4.1 2k−p designs of resolution-III 36
2.4.2 Plackett-Burman designs of resolution-III 39
2.5 Regression analysis: factor interactions 40
2.6 Designs allowing two-factor interactions: resolution-IV 42
2.7 Designs for two-factor interactions: resolution-V 46
2.8 Regression analysis: second-order polynomials 49
2.9 Designs for second-degree polynomials: Central Composite Designs (CCDs) 50
2.10 Optimal designs and other designs 51
2.11 Validation of metamodels 54
2.11.1 Coefficients of determination and correlation coefficients 54
2.11.2 Cross-validation 57
2.12 More simulation applications 63
2.13 Conclusions 66
2.14 Appendix: coding of nominal factors 66
2.15 Solutions for exercises 69
3 Classic assumptions revisited 73
3.1 Introduction 73
3.2 Multivariate simulation output 74
3.2.1 Designs for multivariate simulation output 77
3.3 Nonnormal simulation output 78
3.3.1 Realistic normality assumption? 78
3.3.2 Testing the normality assumption 79
3.3.3 Transformations of simulation I/O data, jackknifing, and bootstrapping 80
3.4 Heterogeneous simulation output variances 87
3.4.1 Realistic constant variance assumption? 87
3.4.2 Testing for constant variances 88
3.4.3 Variance stabilizing transformations 89
3.4.4 LS estimators in case of heterogeneous variances 89
3.4.5 Designs in case of heterogeneous variances 92
3.5 Common random numbers (CRN) 93
3.5.1 Realistic CRN assumption? 94
3.5.2 Alternative analysis methods 94
3.5.3 Designs in case of CRN 96
3.6 Nonvalid low-order polynomial metamodel 97
3.6.1 Testing the validity of the metamodel 97
3.6.2 Transformations of independent and dependent regression variables 98
3.6.3 Adding high-order terms to a low-order polynomial metamodel 98
3.6.4 Nonlinear metamodels 99
3.7 Conclusions 99
3.8 Solutions for exercises 100
4 Simulation optimization 101
4.1 Introduction 101
4.2 RSM: classic variant 105
4.3 Generalized RSM: multiple outputs and constraints 110
4.4 Testing an estimated optimum: KKT conditions 116
4.5 Risk analysis 123
4.5.1 Latin Hypercube Sampling (LHS) 126
4.6 Robust optimization: Taguchian approach 130
4.6.1 Case study: Ericsson’s supply chain 135
4.7 Conclusions 137
4.8 Solutions for exercises 138
5 Kriging metamodels 139
5.1 Introduction 139
5.2 Kriging basics 140
5.3 Kriging: new results 147
5.4 Designs for Kriging 149
5.4.1 Predictor variance in random simulation 151
5.4.2 Predictor variance in deterministic simulation 152
5.4.3 Related designs 154
5.5 Conclusions 155
5.6 Solutions for exercises 156
6 Screening designs 157
6.1 Introduction 157
6.2 Sequential Bifurcation 160
6.2.1 Outline of simplest SB 160
6.2.2 Mathematical details of simplest SB 165
6.2.3 Case study: Ericsson’s supply chain 167
6.2.4 SB with two-factor interactions 169
6.3 Conclusions 171
6.4 Solutions for exercises 172
7 Epilogue 173
References 175
Index 211
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