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疫情物流建模:运筹学的新视角(英文版)
  • 书号:9787030625878
    作者:刘明等
  • 外文书名:
  • 装帧:圆脊精装
    开本:B5
  • 页数:272
    字数:
    语种:en
  • 出版社:科学出版社
    出版时间:1900-01-01
  • 所属分类:
  • 定价: ¥159.00元
    售价: ¥127.20元
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目录

  • Contents
    Chapter 1 Basic concept of epidemic-logistics 1
    1.1 Basic knowledge of epidemic dynamics 1
    1.1.1 Adequate contact rate and incidence 2
    1.1.2 Basic reproduction number 3
    1.2 Epidemics control and logistics operations 4
    1.2.1 Preparedness 4
    1.2.2 Outbreak investigation 5
    1.2.3 Response 6
    1.2.4 Evaluation 7
    1.3 Future directions for epidemic-logistics research 8
    References 10
    Chapter 2 Epidemic dynamics modeling and analysis 13
    2.1 Epidemic dynamics in anti-bioterrorism system 13
    2.1.1 Introduction 13
    2.1.2 SIQRS epidemic diffusion model 15
    2.1.3 SEIQRS epidemic diffusion model 19
    2.1.4 Computational experiments and result analysis 21
    2.2 Epidemic dynamics modeling for influenza 24
    2.2.1 Introduction 24
    2.2.2 SEIRS model with small world network 25
    2.2.3 Emergency demand base on epidemic diffusion model 29
    2.2.4 Numerical test 30
    2.3 Epidemic dynamics considering population migration 33
    2.3.1 Introduction 33
    2.3.2 Epidemic model with population migration 34
    2.3.3 Model analysis 35
    2.3.4 Numerical test 40
    References 43
    Chapter 3 Mixed distribution mode for emergency resources in anti-bioterrorism system 47
    3.1 Introduction 47
    3.2 Literature review 48
    3.2.1 Literature related to epidemic prevention and control 49
    3.2.2 Literature related to emergency distribution 50
    3.3 Demand forecasting based on epidemic dynamics 51
    3.3.1 SEIQRS model based on small-world network 51
    3.3.2 Demand for emergency resources 52
    3.4 Model formulations 53
    3.4.1 Point-to-point distribution mode with no vehicle constraints 53
    3.4.2 The multi-depot, multiple traveling salesmen distribution mode with vehicle constraints 54
    3.4.3 The mixed-collaborative distribution mode 56
    3.5 Solution procedures 58
    3.5.1 Operating instructions for genetic algorithms 58
    3.5.2 The solution procedure 59
    3.6 Computational experiments and result analysis 60
    3.6.1 Comparison and analysis for each stockpile depot 61
    3.6.2 Comparison and analysis for total distance and timeliness 63
    3.7 Conclusions 64
    References 64
    Chapter 4 Epidemic logistics with demand information updating—ModelⅠ: Medical resource is enough 67
    4.1 Introduction 67
    4.2 Literature review 68
    4.2.1 Epidemic diffusion modeling 68
    4.2.2 Medical resource allocation modeling 69
    4.3 The mathematical model 70
    4.3.1 SEIRS epidemic diffusion model 71
    4.3.2 The forecasting model for the time-varying demand 73
    4.3.3 Time-space network of the medicine logistics 74
    4.4 Solution methodology 77
    4.5 Numerical tests 78
    4.5.1 A numerical example 78
    4.5.2 Model comparison 81
    4.5.3 Sensitivity analysis 83
    4.6 Conclusions 84
    References 85
    Chapter 5 Epidemic logistics with demand information updating—ModelⅡ: Medical resource is limited 88
    5.1 Introduction 88
    5.2 Epidemic diffusion analysis and demand forecasting 91
    5.2.1 Influenza diffusion analysis 91
    5.2.2 Demand forecasting 93
    5.3 The dynamic medical resources allocation model 95
    5.3.1 Model specification 95
    5.3.2 Notation 96
    5.3.3 Model formulation 96
    5.3.4 Solution procedure 97
    5.4 Numerical example and discussion 97
    5.4.1 Numerical example 97
    5.4.2 Comparison and discussion 100
    5.4.3 A short sensitivity analysis 102
    5.5 Conclusions 102
    References 103
    Chapter 6 Integrated optimization model for two-level epidemic-logistics network 106
    6.1 Introduction 106
    6.2 Problem description 107
    6.2.1 SEIR epidemic diffusion model 108
    6.2.2 Forecasting model for the time-varying demand 109
    6.2.3 Forecasting model for the time-varying inventory 111
    6.3 Optimization model and solution methodology 111
    6.3.1 The integrated optimization model 111
    6.3.2 Solution methodology 113
    6.4 A numerical example and implications 117
    6.4.1 A numerical example 117
    6.4.2 A short sensitivity analysis 122
    6.5 Conclusions 123
    References 124
    Chapter 7 Integrated optimization model for three-level epidemic-logistics network 125
    7.1 Introduction 125
    7.2 Problem description 127
    7.2.1 Model framework 127
    7.2.2 Time-varying forecasting method for the dynamic demand 128
    7.2.3 Dynamic demand and inventory for the UHD 129
    7.3 Optimization model and solution procedure 129
    7.3.1 Optimization model 129
    7.3.2 Solution procedure 131
    7.4 Numerical example 132
    7.5 Conclusions 136
    References 137
    Chapter 8 A novel FPEA model for medical resources allocation in an epidemic control 139
    8.1 Introduction 139
    8.2 The mathematical model 141
    8.2.1 Forecasting phase 142
    8.2.2 Planning phase 144
    8.2.3 Execution phase 150
    8.2.4 Loop closed 150
    8.3 Numerical example 152
    8.3.1 Test for forecasting phase 152
    8.3.2 Test for logistic planning phase 153
    8.3.3 Test for adjustment phase 157
    8.4 Conclusions 159
    References 159
    Chapter 9 Integrated planning for public health emergencies: A modified model for controlling H1N1 pandemic 162
    9.1 Introduction 162
    9.2 Literature review 163
    9.3 Model formulation 166
    9.3.1 Epidemic compartmental model 166
    9.3.2 Resource allocation model 169
    9.3.3 Model solution 170
    9.4 Case study 171
    9.4.1 Background and parameters setting 171
    9.4.2 Test results 173
    9.4.3 Discussion 175
    9.5 Conclusions 177
    References 179
    Chapter 10 Logistics planning for hospital pharmacy trusteeship under a hybrid of uncertainties 182
    10.1 Introduction 182
    10.2 Literature review 184
    10.2.1 VMI in hospital 184
    10.2.2 Logistics planning with different influence factors 185
    10.3 Time-space network model 187
    10.3.1 Network structure 187
    10.3.2 Deterministic planning model 190
    10.3.3 Stochastic planning model 192
    10.4 Solution algorithms and evaluation methods 195
    10.4.1 Solution method for DPM 195
    10.4.2 Solution method for SPM 196
    10.4.3 Evaluation method 197
    10.5 Numerical tests 197
    10.5.1 Data setting 197
    10.5.2 Test results 197
    10.5.3 Sensitivity analysis 200
    10.6 Conclusions 202
    References 203
    Chapter 11 Medical resources order and shipment in community health service centers 206
    11.1 Introduction 206
    11.2 Literature review 207
    11.3 Modeling approach 208
    11.3.1 Network structure 209
    11.3.2 The deterministic model (DM) 210
    11.3.3 The stochastic model (SM) 211
    11.4 Solution procedure and evaluation method 212
    11.4.1 Solution procedure 212
    11.4.2 Evaluation method 213
    11.5 Numerical tests 214
    11.5.1 Parameters setting 214
    11.5.2 Test results 214
    11.5.3 Sensitivity analysis 215
    11.6 Conclusions 217
    References 218
    Chapter 12 Three short time-space network models for medicine management 220
    12.1 ModelⅠ: A basic time-space network model 220
    12.1.1 Introduction 220
    12.1.2 The time-space network model 221
    12.1.3 Solution algorithm 224
    12.1.4 Numerical tests 224
    12.1.5 Conclusions 226
    12.2 Model Ⅱ: An improved time-space network model 227
    12.2.1 Introduction 227
    12.2.2 Model formulation 228
    12.2.3 The solution procedure 232
    12.2.4 Numerical tests 233
    12.2.5 Conclusions 236
    12.3 Model Ⅲ: A chance-constrained programming model based on time-space network 237
    12.3.1 Introduction 237
    12.3.2 Model formulation 237
    12.3.3 The solution procedure 240
    12.3.4 Numerical tests 241
    12.3.5 Conclusions 244
    References 244
    Chapter 13 Epidemic-logistics network considering time windows and service level 246
    13.1 Emergency materials distribution with time windows 246
    13.1.1 Introduction 246
    13.1.2 SIR epidemic model 248
    13.1.3 Emergency materials distribution network with time windows 248
    13.1.4 Numerical tests 250
    13.1.5 Discussion 253
    13.1.6 Conclusions 255
    13.2 An improved location-allocation model for emergency logistics network design 255
    13.2.1 Introduction 256
    13.2.2 Model formulation 257
    13.2.3 Solution procedure 260
    13.2.4 Numerical test 260
    13.2.5 Conclusions 263
    References 263
    Appendix A 266
    Appendix B 268
    B1 Model validation 268
    B2 Optimization results with different budget sizes 270
    B3 Impact of different intervention starting dates 271
    Reference 272
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