Introduction to distribution logistics:
This text presents the basics of distribution logistics (DL) in both a qualitative and quantitative manner so as to reach out to a multitude of reader backgrounds. Devoid of solid quantitative books in the marketplace, this book fills a gap. The authors do not encourage the undiscriminating use of s...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley-Interscience
2007
|
| Schriftenreihe: | Statistics in practice
|
| Schlagworte: | |
| Online-Zugang: | Beschreibung für Leser Table of contents only Contributor biographical information Publisher description Inhaltsverzeichnis |
| Zusammenfassung: | This text presents the basics of distribution logistics (DL) in both a qualitative and quantitative manner so as to reach out to a multitude of reader backgrounds. Devoid of solid quantitative books in the marketplace, this book fills a gap. The authors do not encourage the undiscriminating use of sophisticated models and algorithms to the detriment of intuition and common sense. The emphases throughout the book are on the variety and complexity of issues and sub problems surrounding DL and their limitations and scope of applicability. The context in which a firm operates, its strategic positioning, and the managerial levers that decision makers may act upon represent key discussions and provide a unified approach to the subject matter. |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XVI, 587 S. graph. Darst. |
| ISBN: | 9780471750444 0471750441 |
Internformat
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| 245 | 1 | 0 | |a Introduction to distribution logistics |c Paolo Brandimarte ; Giulio Zotteri |
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| 520 | 3 | |a This text presents the basics of distribution logistics (DL) in both a qualitative and quantitative manner so as to reach out to a multitude of reader backgrounds. Devoid of solid quantitative books in the marketplace, this book fills a gap. The authors do not encourage the undiscriminating use of sophisticated models and algorithms to the detriment of intuition and common sense. The emphases throughout the book are on the variety and complexity of issues and sub problems surrounding DL and their limitations and scope of applicability. The context in which a firm operates, its strategic positioning, and the managerial levers that decision makers may act upon represent key discussions and provide a unified approach to the subject matter. | |
| 650 | 4 | |a Mathematik | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Network analysis (Planning) |x Mathematics | |
| 650 | 4 | |a Production scheduling |x Statistical methods | |
| 650 | 4 | |a Business logistics |x Statistical methods | |
| 650 | 4 | |a Traffic flow |x Mathematical models | |
| 650 | 4 | |a Physical distribution of goods |x Mathematics | |
| 650 | 4 | |a Distribution (Probability theory) | |
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Datensatz im Suchindex
| _version_ | 1804137192965013504 |
|---|---|
| adam_text | Contents
Preface xiii
1 Supply Chain Management 1
1.1 What do we mean by logistics? 1
1.1.1 Plan of the chapter 4
1.2 Structure of production/distribution networks 6
1.3 Competition factors, cost drivers, and strategy 9
1.3.1 Competition factors 9
1.3.2 Cost drivers 12
1.3.3 Strategy 16
1.4 The role of inventories 18
1.4 1 A classical model: Economic order
quantity 19
1.4 2 Capacity induced stock 25
1.5 Dealing with uncertainty 26
1.5.1 Setting safety stocks 21
1.5.2 A two stage decision process: Production
planning in an assemble to order
environment 30
1.5.3 Inventory deployment 39
V
vi CONTENTS
1.6 Physical flows and transportation 40
1.7 Information flows and decision rights 41
1.8 Time horizons and hierarchical levels 4%
1.9 Decision approaches 44
1.10 Quantitative models and methods 48
1.11 For further reading 50
References 51
2 Network Design and Transportation 53
2.1 The role of intermediate nodes in a distribution
network 55
2.1.1 The risk pooling effect: reducing the
uncertainty level 56
2.1.2 The role of distribution centers and transit
points in transportation optimization 59
2.2 Location and flow optimization models 11
2.2.1 The transportation problem 72
2.2.2 The minimum cost flow problem 74
2.2.3 The plant location problem 76
2.2.4 Putting it all together 80
2.3 Models involving nonlinear costs 83
W.2.4 Continuous space location models 88
W.2.5 Retail store location models 88
2.6 For Further Reading 89
References 89
3 Forecasting 91
3.1 Introduction 91
3.2 The variable to be predicted 93
3.2.1 The forecasting process 98
3.3 Metrics for forecast errors 103
3.3.1 The Mean Error 104
3.3.2 Mean Absolute Deviation 104
3.3.3 Root Mean Square Error 106
3.3.4 Mean Percentage Error and Mean
Absolute Percentage Error 107
3.3.5 ME%, MAD%, RMSE% 110
3.3.6 Theil s U statistic 112
3.3.7 Using metrics of forecasting accuracy 113
CONTENTS vii
3.4 A classification of forecasting methods 116
3.5 Moving Average 120
3.5.1 The demand model 120
3.5.2 The algorithm 121
3.5.3 Setting the parameter 121
3.5.4 Drawbacks and limitations 125
3.6 Simple exponential smoothing 127
3.6.1 The demand model 127
3.6.2 The algorithm 128
3.6.3 Setting the parameter 132
3.6.4 Initialization 134
3.6.5 Drawbacks and limitations 138
3.7 Exponential Smoothing with Trend 138
3.7.1 The demand model 138
3.7.2 The algorithm 138
3.7.3 Setting the parameters 139
3.7.4 Initialization 140
3.7.5 Drawbacks and limitations 142
3.8 Exponential smoothing with seasonality 144
3.8.1 The demand model 144
3.8.2 The algorithm 145
3.8.3 Setting the parameters 147
3.8.4 Initialization 147
3.8.5 Drawbacks and limitations 153
3.9 Smoothing with seasonality and trend 154
3.9.1 The demand model 154
3.9.2 The algorithm 154
3.9.3 Initialization 155
3.10 Simple linear regression 158
3.10.1 Setting up data for regression 165
W.3.11 Forecasting models based on multiple regression 165
3.12 Forecasting demand for new products 166
3.12.1 The Delphi method and the committee
process 166
3.12.2 Lancaster model: forecasting new products
through product features 171
3.12.3 The early sales model 172
3.13 The Bass model 177
3.13.1 Limitations and drawbacks 185
viii CONTENTS
References 185
4 Inventory Management with Deterministic Demand 187
4 1 Introduction 187
4 2 Economic Order Quantity 195
4.3 Robustness of EOQ model 208
44 Case o/LT 0: the (Q,R) model 210
4 5 Case of finite replenishment rate 212
4.6 Multi item EOQ 214
4 6.1 The case of shared ordering costs 215
4 6.2 The multi item case with a constraint on
ordering capacity 217
4 7 Case of nonlinear costs 220
4 8 The case of variable demand with known
variability 225
References 230
5 Inventory Control: The Stochastic Case 233
5.1 Introduction 233
5.2 The newsvendor problem . 245
5.2.1 Extensions of the newsvendor problem 259
5.3 Multi period problems 269
5.4 Fixed quantity: the (Q,R) model 270
5.4 1 Optimization of the (Q,R) model in case
the stockout cost depends on the size of
the stockout 278
5.4.2 (Q,R) system: case of constraint on the
type II service level 284
5.4 3 (Q,R) system: case of constraint on type I
service level 287
5.5 Periodic review: S and (s, S) policies 288
5.6 The S policy 290
5.7 The (s, S) policy 296
S.5.8 Optimization of the (Q,R) model when the cost
of a stockout depends on the occurrence of a
stockout 299
References 301
6 Managing Inventories in Multiechelon Supply Chains 303
6.1 Introduction 303
CONTENTS ix
6.2 Managing multiechelon chains: Installation vs.
Echelon Stock 309
6.2.1 Features of Installation and Echelon Stock
logics 312
6.3 Coordination in the supply chain: the Bullwhip
effect 324
6.4 A linear distribution chain with two echelons and
certain demand 335
6.5 Arborescent chain: transit point with uncertain
demand 342
6.6 A two echelon supply chain in case of stochastic
demand 351
References 357
7 Incentives in the Supply Chain 359
7.1 Introduction 359
7.2 Decisions on price: double marginalization 361
7.2.1 The first best solution: the vertically
integrated firm 362
7.2.2 The vertically disintegrated case:
independent manufacturer and retailer 363
7.2.3 A way out: designing incentive schemes 369
7.3 Decision on price in a competitive environment 372
7.3.1 The vertically disintegrated supply chain:
independent manufacturer and retailer. 373
7.4 Decision on inventories: the newsvendor problem 375
7.4 1 The first best solution: the vertically
integrated firm 375
7.4 2 The vertically disintegrated case:
independent manufacturer and retailer 376
7.4 3 A way out: designing incentives and
reallocating decision rights 378
7.5 Decision on effort to produce and sell the product 384
7.5.1 The first best solution: the vertically
integrated firm 385
7.5.2 The vertically disintegrated case:
independent retailer and manufacturer 386
7.5.3 A way out: designing incentive schemes. 389
7.5.4 The case of efforts both at the upstream
and downstream stage 390
7.6 Concluding remarks 393
x CONTENTS
References 394
8 Vehicle Routing 397
8.1 Network routing problems: The TSP 398
8.1.1 Other network routing problems 402
8.2 Solution methods for symmetric TSP 403
8.2.1 Nearest neighbor heuristic 404
8.2.2 Insertion based heuristics 405
8.2.3 Local search methods 407
8.3 Solution methods for basic VRP 412
8.3.1 Constructive methods for VRP 4M
8.3.2 Decomposition methods for VRP: cluster
first, route second 421
8.4 Additional features of real life VRP 425
8.4 1 Constructive methods for the VRP with
time windows 427
8.5 Final remarks 430
8.6 For further reading 430
References 431
Appendix A A Quick Tour of Probability and Statistics 433
A.I Sample space, events, and probability 434
A.2 Conditional probability and independence 438
A.3 Discrete random variables 442
A.3.1 A few examples of discrete distributions 446
A.4 Continuous random variables 452
A.4 1 Some continuous distributions 457
A.5 Jointly distributed random variables 461
A.6 Independence, covariance, and conditional
expectation 463
A.6.1 Independent random variables 463
A.6.2 Covariance and correlation 465
A.6.3 Distributions obtained from the normal
and the central limit theorem 467
A.6.4 Conditional expectation 4^1
A.7 Stochastic processes 4?5
A.8 Parameter estimation 48I
A.8.1 Sample covariance and correlation 485
A.8.2 Confidence intervals 490
CONTENTS xi
A.9 Hypothesis testing 494
A.9.1 An example of a nonparametric test: the
chi square test 498
A.9.2 Testing hypotheses about the difference in
the mean of two populations 499
A. 10 Simple linear regression 501
A. 10.1 Best fitting by least squares 503
A. 10.2 Analyzing properties of regression
estimators 506
A. 10.3 Confidence intervals and hypothesis
testing for regression estimators 519
A. 10.4 Performance measures for linear
regression 521
A. 10.5 Verification of the underlying assumptions 524
A. 10.6 Using linear regression to estimate
nonlinear relationships 528
W.A.ll Multiple linear regression 533
A.12 For further reading 533
References 534
Appendix B An Even Quicker Tour in Mathematical
Programming 535
B. 1 Role and limitations of optimization models 537
B.2 Optimization models 544
B.3 Convex sets and functions 548
B.4 Nonlinear programming 553
B.4 1 The case of inequality constraints 556
B.4 2 An economic interpretation of Lagrange
multipliers: shadow prices 559
B. 5 Linear programming 562
B. 6 Integer linear programming 564
B.6.1 Branch and bound methods 566
B.6.2 Model building in integer programming 571
B. 7 Elements of multiobjective optimization 575
B.8 For further reading 579
References 579
Index 581
|
| adam_txt |
Contents
Preface xiii
1 Supply Chain Management 1
1.1 What do we mean by logistics? 1
1.1.1 Plan of the chapter 4
1.2 Structure of production/distribution networks 6
1.3 Competition factors, cost drivers, and strategy 9
1.3.1 Competition factors 9
1.3.2 Cost drivers 12
1.3.3 Strategy 16
1.4 The role of inventories 18
1.4 1 A classical model: Economic order
quantity 19
1.4 2 Capacity induced stock 25
1.5 Dealing with uncertainty 26
1.5.1 Setting safety stocks 21
1.5.2 A two stage decision process: Production
planning in an assemble to order
environment 30
1.5.3 Inventory deployment 39
V
vi CONTENTS
1.6 Physical flows and transportation 40
1.7 Information flows and decision rights 41
1.8 Time horizons and hierarchical levels 4%
1.9 Decision approaches 44
1.10 Quantitative models and methods 48
1.11 For further reading 50
References 51
2 Network Design and Transportation 53
2.1 The role of intermediate nodes in a distribution
network 55
2.1.1 The risk pooling effect: reducing the
uncertainty level 56
2.1.2 The role of distribution centers and transit
points in transportation optimization 59
2.2 Location and flow optimization models 11
2.2.1 The transportation problem 72
2.2.2 The minimum cost flow problem 74
2.2.3 The plant location problem 76
2.2.4 Putting it all together 80
2.3 Models involving nonlinear costs 83
W.2.4 Continuous space location models 88
W.2.5 Retail store location models 88
2.6 For Further Reading 89
References 89
3 Forecasting 91
3.1 Introduction 91
3.2 The variable to be predicted 93
3.2.1 The forecasting process 98
3.3 Metrics for forecast errors 103
3.3.1 The Mean Error 104
3.3.2 Mean Absolute Deviation 104
3.3.3 Root Mean Square Error 106
3.3.4 Mean Percentage Error and Mean
Absolute Percentage Error 107
3.3.5 ME%, MAD%, RMSE% 110
3.3.6 Theil's U statistic 112
3.3.7 Using metrics of forecasting accuracy 113
CONTENTS vii
3.4 A classification of forecasting methods 116
3.5 Moving Average 120
3.5.1 The demand model 120
3.5.2 The algorithm 121
3.5.3 Setting the parameter 121
3.5.4 Drawbacks and limitations 125
3.6 Simple exponential smoothing 127
3.6.1 The demand model 127
3.6.2 The algorithm 128
3.6.3 Setting the parameter 132
3.6.4 Initialization 134
3.6.5 Drawbacks and limitations 138
3.7 Exponential Smoothing with Trend 138
3.7.1 The demand model 138
3.7.2 The algorithm 138
3.7.3 Setting the parameters 139
3.7.4 Initialization 140
3.7.5 Drawbacks and limitations 142
3.8 Exponential smoothing with seasonality 144
3.8.1 The demand model 144
3.8.2 The algorithm 145
3.8.3 Setting the parameters 147
3.8.4 Initialization 147
3.8.5 Drawbacks and limitations 153
3.9 Smoothing with seasonality and trend 154
3.9.1 The demand model 154
3.9.2 The algorithm 154
3.9.3 Initialization 155
3.10 Simple linear regression 158
3.10.1 Setting up data for regression 165
W.3.11 Forecasting models based on multiple regression 165
3.12 Forecasting demand for new products 166
3.12.1 The Delphi method and the committee
process 166
3.12.2 Lancaster model: forecasting new products
through product features 171
3.12.3 The early sales model 172
3.13 The Bass model 177
3.13.1 Limitations and drawbacks 185
viii CONTENTS
References 185
4 Inventory Management with Deterministic Demand 187
4 1 Introduction 187
4 2 Economic Order Quantity 195
4.3 Robustness of EOQ model 208
44 Case o/LT 0: the (Q,R) model 210
4 5 Case of finite replenishment rate 212
4.6 Multi item EOQ 214
4 6.1 The case of shared ordering costs 215
4 6.2 The multi item case with a constraint on
ordering capacity 217
4 7 Case of nonlinear costs 220
4 8 The case of variable demand with known
variability 225
References 230
5 Inventory Control: The Stochastic Case 233
5.1 Introduction 233
5.2 The newsvendor problem . 245
5.2.1 Extensions of the newsvendor problem 259
5.3 Multi period problems 269
5.4 Fixed quantity: the (Q,R) model 270
5.4 1 Optimization of the (Q,R) model in case
the stockout cost depends on the size of
the stockout 278
5.4.2 (Q,R) system: case of constraint on the
type II service level 284
5.4 3 (Q,R) system: case of constraint on type I
service level 287
5.5 Periodic review: S and (s, S) policies 288
5.6 The S policy 290
5.7 The (s, S) policy 296
S.5.8 Optimization of the (Q,R) model when the cost
of a stockout depends on the occurrence of a
stockout 299
References 301
6 Managing Inventories in Multiechelon Supply Chains 303
6.1 Introduction 303
CONTENTS ix
6.2 Managing multiechelon chains: Installation vs.
Echelon Stock 309
6.2.1 Features of Installation and Echelon Stock
logics 312
6.3 Coordination in the supply chain: the Bullwhip
effect 324
6.4 A linear distribution chain with two echelons and
certain demand 335
6.5 Arborescent chain: transit point with uncertain
demand 342
6.6 A two echelon supply chain in case of stochastic
demand 351
References 357
7 Incentives in the Supply Chain 359
7.1 Introduction 359
7.2 Decisions on price: double marginalization 361
7.2.1 The first best solution: the vertically
integrated firm 362
7.2.2 The vertically disintegrated case:
independent manufacturer and retailer 363
7.2.3 A way out: designing incentive schemes 369
7.3 Decision on price in a competitive environment 372
7.3.1 The vertically disintegrated supply chain:
independent manufacturer and retailer. 373
7.4 Decision on inventories: the newsvendor problem 375
7.4 1 The first best solution: the vertically
integrated firm 375
7.4 2 The vertically disintegrated case:
independent manufacturer and retailer 376
7.4 3 A way out: designing incentives and
reallocating decision rights 378
7.5 Decision on effort to produce and sell the product 384
7.5.1 The first best solution: the vertically
integrated firm 385
7.5.2 The vertically disintegrated case:
independent retailer and manufacturer 386
7.5.3 A way out: designing incentive schemes. 389
7.5.4 The case of efforts both at the upstream
and downstream stage 390
7.6 Concluding remarks 393
x CONTENTS
References 394
8 Vehicle Routing 397
8.1 Network routing problems: The TSP 398
8.1.1 Other network routing problems 402
8.2 Solution methods for symmetric TSP 403
8.2.1 Nearest neighbor heuristic 404
8.2.2 Insertion based heuristics 405
8.2.3 Local search methods 407
8.3 Solution methods for basic VRP 412
8.3.1 Constructive methods for VRP 4M
8.3.2 Decomposition methods for VRP: cluster
first, route second 421
8.4 Additional features of real life VRP 425
8.4 1 Constructive methods for the VRP with
time windows 427
8.5 Final remarks 430
8.6 For further reading 430
References 431
Appendix A A Quick Tour of Probability and Statistics 433
A.I Sample space, events, and probability 434
A.2 Conditional probability and independence 438
A.3 Discrete random variables 442
A.3.1 A few examples of discrete distributions 446
A.4 Continuous random variables 452
A.4 1 Some continuous distributions 457
A.5 Jointly distributed random variables 461
A.6 Independence, covariance, and conditional
expectation 463
A.6.1 Independent random variables 463
A.6.2 Covariance and correlation 465
A.6.3 Distributions obtained from the normal
and the central limit theorem 467
A.6.4 Conditional expectation 4^1
A.7 Stochastic processes 4?5
A.8 Parameter estimation 48I
A.8.1 Sample covariance and correlation 485
A.8.2 Confidence intervals 490
CONTENTS xi
A.9 Hypothesis testing 494
A.9.1 An example of a nonparametric test: the
chi square test 498
A.9.2 Testing hypotheses about the difference in
the mean of two populations 499
A. 10 Simple linear regression 501
A. 10.1 Best fitting by least squares 503
A. 10.2 Analyzing properties of regression
estimators 506
A. 10.3 Confidence intervals and hypothesis
testing for regression estimators 519
A. 10.4 Performance measures for linear
regression 521
A. 10.5 Verification of the underlying assumptions 524
A. 10.6 Using linear regression to estimate
nonlinear relationships 528
W.A.ll Multiple linear regression 533
A.12 For further reading 533
References 534
Appendix B An Even Quicker Tour in Mathematical
Programming 535
B. 1 Role and limitations of optimization models 537
B.2 Optimization models 544
B.3 Convex sets and functions 548
B.4 Nonlinear programming 553
B.4 1 The case of inequality constraints 556
B.4 2 An economic interpretation of Lagrange
multipliers: shadow prices 559
B. 5 Linear programming 562
B. 6 Integer linear programming 564
B.6.1 Branch and bound methods 566
B.6.2 Model building in integer programming 571
B. 7 Elements of multiobjective optimization 575
B.8 For further reading 579
References 579
Index 581 |
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| author | Brandimarte, Paolo Zotteri, Giulio |
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| genre | (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Lehrbuch |
| id | DE-604.BV022950087 |
| illustrated | Illustrated |
| index_date | 2024-07-02T19:01:54Z |
| indexdate | 2024-07-09T21:08:24Z |
| institution | BVB |
| isbn | 9780471750444 0471750441 |
| language | English |
| lccn | 2007006008 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016154568 |
| oclc_num | 85018295 |
| open_access_boolean | |
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| owner_facet | DE-703 DE-1050 DE-M347 DE-634 DE-1049 DE-83 DE-Aug4 |
| physical | XVI, 587 S. graph. Darst. |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Wiley-Interscience |
| record_format | marc |
| series2 | Statistics in practice |
| spelling | Brandimarte, Paolo Verfasser aut Introduction to distribution logistics Paolo Brandimarte ; Giulio Zotteri Hoboken, NJ Wiley-Interscience 2007 XVI, 587 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Statistics in practice Includes bibliographical references and index This text presents the basics of distribution logistics (DL) in both a qualitative and quantitative manner so as to reach out to a multitude of reader backgrounds. Devoid of solid quantitative books in the marketplace, this book fills a gap. The authors do not encourage the undiscriminating use of sophisticated models and algorithms to the detriment of intuition and common sense. The emphases throughout the book are on the variety and complexity of issues and sub problems surrounding DL and their limitations and scope of applicability. The context in which a firm operates, its strategic positioning, and the managerial levers that decision makers may act upon represent key discussions and provide a unified approach to the subject matter. Mathematik Mathematisches Modell Network analysis (Planning) Mathematics Production scheduling Statistical methods Business logistics Statistical methods Traffic flow Mathematical models Physical distribution of goods Mathematics Distribution (Probability theory) Distributionslogistik (DE-588)4150252-8 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Distributionslogistik (DE-588)4150252-8 s DE-604 Zotteri, Giulio Verfasser aut http://catdir.loc.gov/catdir/enhancements/fy0739/2007006008-d.html Beschreibung für Leser http://www.loc.gov/catdir/toc/ecip0711/2007006008.html Table of contents only http://www.loc.gov/catdir/enhancements/fy0739/2007006008-b.html Contributor biographical information http://www.loc.gov/catdir/enhancements/fy0739/2007006008-d.html Publisher description HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016154568&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Brandimarte, Paolo Zotteri, Giulio Introduction to distribution logistics Mathematik Mathematisches Modell Network analysis (Planning) Mathematics Production scheduling Statistical methods Business logistics Statistical methods Traffic flow Mathematical models Physical distribution of goods Mathematics Distribution (Probability theory) Distributionslogistik (DE-588)4150252-8 gnd |
| subject_GND | (DE-588)4150252-8 (DE-588)4123623-3 |
| title | Introduction to distribution logistics |
| title_auth | Introduction to distribution logistics |
| title_exact_search | Introduction to distribution logistics |
| title_exact_search_txtP | Introduction to distribution logistics |
| title_full | Introduction to distribution logistics Paolo Brandimarte ; Giulio Zotteri |
| title_fullStr | Introduction to distribution logistics Paolo Brandimarte ; Giulio Zotteri |
| title_full_unstemmed | Introduction to distribution logistics Paolo Brandimarte ; Giulio Zotteri |
| title_short | Introduction to distribution logistics |
| title_sort | introduction to distribution logistics |
| topic | Mathematik Mathematisches Modell Network analysis (Planning) Mathematics Production scheduling Statistical methods Business logistics Statistical methods Traffic flow Mathematical models Physical distribution of goods Mathematics Distribution (Probability theory) Distributionslogistik (DE-588)4150252-8 gnd |
| topic_facet | Mathematik Mathematisches Modell Network analysis (Planning) Mathematics Production scheduling Statistical methods Business logistics Statistical methods Traffic flow Mathematical models Physical distribution of goods Mathematics Distribution (Probability theory) Distributionslogistik Lehrbuch |
| url | http://catdir.loc.gov/catdir/enhancements/fy0739/2007006008-d.html http://www.loc.gov/catdir/toc/ecip0711/2007006008.html http://www.loc.gov/catdir/enhancements/fy0739/2007006008-b.html http://www.loc.gov/catdir/enhancements/fy0739/2007006008-d.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016154568&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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