Principles of inventory management: when you are down to four, order more
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| Hauptverfasser: | , |
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| Format: | Buch |
| Sprache: | English |
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New York, NY [u.a.]
Springer
[2010]
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| Schriftenreihe: | Springer Series in Operations Research and Financial Engineering
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xviii, 339 Seiten Illustrationen |
| ISBN: | 9780387244921 9780387689487 |
Internformat
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| 245 | 1 | 0 | |a Principles of inventory management |b when you are down to four, order more |c John A. Muckstadt ; Amar Sapra |
| 246 | 1 | 3 | |a Models and solutions in inventory management |
| 264 | 1 | |a New York, NY [u.a.] |b Springer |c [2010] | |
| 264 | 4 | |c © 2010 | |
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| 490 | 0 | |a Springer Series in Operations Research and Financial Engineering | |
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| 650 | 4 | |a Inventory control | |
| 650 | 4 | |a Inventory control |x Mathematical models | |
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Datensatz im Suchindex
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|---|---|
| adam_text | Titel: Principles of inventory management
Autor: Muckstadt, John A.
Jahr: 2010
Contents
Inventories Are Everywhere........................................ 1
1.1 The Roles of Inventory......................................... 2
1.2 Fundamental Questions ........................................ 5
1.3 Factors Affecting Inventory Policy Decisions...................... 6
1.3.1 System Structure ....................................... 6
1.3.2 The Items ............................................. 7
1.3.3 Market Characteristics................................... 8
1.3.4 Lead Times............................................ 12
1.3.5 Costs................................................. 12
1.4 Measuring Performance........................................ 15
EOQ Model...................................................... 17
2.1 Model Development: Economic Order Quantity (EOQ) Model........ 18
2.1.1 Robustness of the EOQ Model............................ 22
2.1.2 Reorder Point and Reorder Interval........................ 25
2.2 EOQ Model with Backordering Allowed.......................... 26
2.2.1 The Optimal Cost....................................... 31
2.3 Quantity Discount Model....................................... 31
2.3.1 All Units Discount...................................... 33
2.3.2 An Algorithm to Determine the Optimal Order Quantity for
the All Units Discount Case.............................. 35
2.3.3 Incremental Quantity Discounts........................... 36
2.3.4 An Algorithm to Determine the Optimal Order Quantity for
the Incremental Quantity Discount Case.................... 38
2.4 Lot Sizing When Constraints Exist............................... 40
2.5 Exercises.................................................... 42
xiv Contents
3 Power-of-Two Policies............................................. 47
3.1 Basic Framework.............................................. 48
3.1.1 Power-of-Two Policies................................... 49
3.1.2 P02 Policy for a Single-Stage System...................... 51
3.1.2.1 Cost for the Optimal P02 Policy.................. 53
3.2 Serial Systems................................................ 55
3.2.1 Assumptions and Nomenclature........................... 55
3.2.2 A Mathematical Model for Serial Systems.................. 59
3.2.3 Algorithm to Obtain an Optimal Solution to (RP)............ 64
3.3 Multi-Echelon Distribution Systems.............................. 68
3.3.1 A Mathematical Model for Distribution Systems............. 68
3.3.1.1 Relaxed Problem............................... 69
3.3.2 Powers-of-Two Solution................................. 73
3.4 Joint Replenishment Problem (JRP).............................. 74
3.4.1 A Mathematical Model for Joint Replenishment Systems...... 75
3.4.2 Rounding the Solution to the Relaxed Problem.............. 80
3.5 Exercises .................................................... 82
4 Dynamic Lot Sizing with Deterministic Demand...................... 85
4.1 The Wagner-Whitin (WW) Algorithm............................ 86
4.1.1 Solution Approach...................................... 89
4.1.2 Algorithm............................................. 92
4.1.3 Shortest-Path Representation of the Dynamic Lot Sizing
Problem............................................... 94
4.1.4 Technical Appendix for the Wagner-Whitin Algorithm....... 95
4.2 Wagelmans-Hoesel-Kolen (WHK) Algorithm..................... 96
4.2.1 Model Formulation ..................................... 97
4.2.2 An Order T log T Algorithm for Solving Problem (4.5)........ 98
4.2.3 Algorithm.............................................102
4.3 Heuristic Methods.............................................104
4.3.1 Silver-Meal Heuristic...................................104
4.3.2 Least Unit Cost Heuristic ................................106
4.4 A Comment on the Planning Horizon.............................108
4.5 Exercises....................................................109
5 Single-Period Models..............................................113
5.1 Making Decisions in the Presence of Uncertainty...................114
5.2 An Example..................................................114
5.2.1 The Data..............................................115
5.2.2 The Decision Model.....................................117
Contents xv
5.3 Another Example .............................................124
5.4 Multiple Items................................................127
5.4.1 A General Model.......................................132
5.4.2 Multiple Constraints ....................................135
5.5 Exercises ....................................................136
Inventory Planning over Multiple Time Periods: Linear-Cost Case .....141
6.1 Optimal Policies ..............................................141
6.1.1 The Single-Unit, Single-Customer Approach: Single-Location
Case..................................................142
6.1.1.1 Notation and Definitions.........................142
6.1.1.2 Optimality of Base-Stock Policies.................145
6.1.1.3 Stochastic Lead Times...........................149
6.1.1.4 The Serial Systems Case.........................149
6.1.1.5 Generalized Demand Model......................150
6.1.1.6 Capacity Limitations............................151
6.2 Finding Optimal Stock Levels...................................151
6.2.1 Finite Planning Horizon Analysis..........................151
6.2.2 Constant, Positive Lead Time Case........................159
6.2.3 End-of-Horizon Effects..................................160
6.2.4 Infinite-Horizon Analysis ................................161
6.2.5 Lost Sales.............................................162
6.3 Capacity Limited Systems......................................163
6.3.1 The Shortfall Distribution................................164
6.3.1.1 General Properties..............................164
6.3.2 Discrete Demand Case...................................166
6.3.3 An Example ...........................................171
6.4 A Serial System...............................................173
6.4.1 An Echelon-Based Approach for Managing Inventories in
Serial Systems .........................................174
6.4.1.1 A Decision Model..............................175
6.4.1.2 A Dynamic Programming Formulation of the
Decision Problem...............................176
6.4.1.3 An Algorithm for Computing Optimal Echelon
Stock Levels...................................180
6.4.1.4 Solving the Oil Rig Problem: The Stationary
Demand Case..................................180
6.5 Exercises ....................................................181
Contents
Background Concepts: An Introduction to the (.v ? 1. .v) Policy under
Poisson Demand..................................................185
7.1 Steady State..................................................186
7.1.1 Backorder Case.........................................188
7.1.2 Lost Sales Case.........................................190
7.2 Performance Measures.........................................193
7.3 Properties of the Performance Measures ..........................198
7.4 Finding Stock Levels in (s ? l,s) Policy Managed Systems:
Optimization Problem Formulations and Solution Algorithms........202
7.4.1 First Example: Minimize Expected Backorders Subject to an
Inventory Investment Constraint...........................202
7.4.2 Second Example: Maximize Expected System Average Fill
Rate Subject to an Inventory Investment Constraint...........206
7.5 Exercises ....................................................208
A Tactical Planning Model for Managing Recoverable Items in
Multi-Echelon Systems............................................211
8.1 The METRIC System..........................................212
8.1.1 System Operation and Definitions.........................213
8.1.2 The Optimization Problem...............................213
8.1.2.1 Approximating the Stationary Probability
Distribution for the Number of LRUs in Resupply.... 217
8.1.2.2 Finding Depot and Base LRU Stock Levels.........221
8.2 Waiting Time Analysis.........................................230
8.3 Exercises ....................................................234
Reorder Point, Lot Size Models: The Continuous Review Case.........237
9.1 An Approximate Model When Backordering Is Permitted............239
9.1.1 Assumptions...........................................239
9.1.2 Constructing the Model..................................240
9.1.3 Finding Q* and r*.......................................242
9.1.4 Convexity of the Objective Function.......................244
9.1.5 Lead Time Demand Is Normally Distributed ................246
9.1.6 Alternative Heuristics for Computing Lot Sizes and Reorder
Points.................................................248
9.1.7 Final Comments on the Approximate Model ................253
9.2 An Exact Model ..............................................253
9.2.1 Determining the Stationary Distribution of the Inventory
Position Random Variable................................254
Contents xvii
9.2.2 Determining the Stationary Distribution of the Net Inventory
Random Variable.......................................255
9.2.3 Computing Performance Measures ........................256
9.2.4 Average Annual Cost Expression..........................258
9.2.5 Waiting Time Analysis ..................................258
9.2.6 Continuous Approximations: The General Case..............260
9.2.7 A Continuous Approximation: Normal Distribution ..........262
9.2.8 Another Continuous Approximation: Laplace Distribution.....264
9.2.9 Optimization...........................................266
9.2.9.1 Normal Demand Model..........................267
9.2.9.2 Laplace Demand Model .........................270
9.2.9.3 Exact Poisson Model............................271
9.2.10 Additional Observations: Compound Poisson Demand
Process, Uncertain Lead Times............................273
9.2.10.1 Finding the Stationary Distribution of the Inventory
Position Random Variable When an (nQ,r) Policy
Is Followed....................................275
9.2.10.2 Establishing the Probability Distribution of the
Inventory Position Random Variable When an (s,S)
Policy Is Employed.............................276
9.2.10.3 Constructing an Objective Function................278
9.2.11 Stochastic Lead Times...................................280
9.3 A Multi-Item Model...........................................282
9.3.1 Model 1...............................................283
9.3.2 Model 2...............................................285
9.3.3 Model 3...............................................285
9.3.4 Model 4...............................................286
9.3.5 Finding 0,.............................................287
9.4 Exercises ....................................................287
10 Lot Sizing Models: The Periodic Review Case........................293
10.1 Notation.....................................................294
10.2 An Approximation Algorithm...................................296
10.2.1 Algorithm.............................................296
10.3 Algorithm for Computing a Stationary Policy......................301
10.3.1 A Primer on Dynamic Programming with an Average Cost
Criterion ..............................................302
10.3.2 Formulation and Background Results......................302
10.3.3 Algorithm.............................................307
10.4 Proof of Theorem 10.1.........................................310
xviii Contents
10.5 A Heuristic Method for Calculating s and S........................314
10.6 Exercises ....................................................316
References............................................................319
Index................................................................337
|
| adam_txt |
Titel: Principles of inventory management
Autor: Muckstadt, John A.
Jahr: 2010
Contents
Inventories Are Everywhere. 1
1.1 The Roles of Inventory. 2
1.2 Fundamental Questions . 5
1.3 Factors Affecting Inventory Policy Decisions. 6
1.3.1 System Structure . 6
1.3.2 The Items . 7
1.3.3 Market Characteristics. 8
1.3.4 Lead Times. 12
1.3.5 Costs. 12
1.4 Measuring Performance. 15
EOQ Model. 17
2.1 Model Development: Economic Order Quantity (EOQ) Model. 18
2.1.1 Robustness of the EOQ Model. 22
2.1.2 Reorder Point and Reorder Interval. 25
2.2 EOQ Model with Backordering Allowed. 26
2.2.1 The Optimal Cost. 31
2.3 Quantity Discount Model. 31
2.3.1 All Units Discount. 33
2.3.2 An Algorithm to Determine the Optimal Order Quantity for
the All Units Discount Case. 35
2.3.3 Incremental Quantity Discounts. 36
2.3.4 An Algorithm to Determine the Optimal Order Quantity for
the Incremental Quantity Discount Case. 38
2.4 Lot Sizing When Constraints Exist. 40
2.5 Exercises. 42
xiv Contents
3 Power-of-Two Policies. 47
3.1 Basic Framework. 48
3.1.1 Power-of-Two Policies. 49
3.1.2 P02 Policy for a Single-Stage System. 51
3.1.2.1 Cost for the Optimal P02 Policy. 53
3.2 Serial Systems. 55
3.2.1 Assumptions and Nomenclature. 55
3.2.2 A Mathematical Model for Serial Systems. 59
3.2.3 Algorithm to Obtain an Optimal Solution to (RP). 64
3.3 Multi-Echelon Distribution Systems. 68
3.3.1 A Mathematical Model for Distribution Systems. 68
3.3.1.1 Relaxed Problem. 69
3.3.2 Powers-of-Two Solution. 73
3.4 Joint Replenishment Problem (JRP). 74
3.4.1 A Mathematical Model for Joint Replenishment Systems. 75
3.4.2 Rounding the Solution to the Relaxed Problem. 80
3.5 Exercises . 82
4 Dynamic Lot Sizing with Deterministic Demand. 85
4.1 The Wagner-Whitin (WW) Algorithm. 86
4.1.1 Solution Approach. 89
4.1.2 Algorithm. 92
4.1.3 Shortest-Path Representation of the Dynamic Lot Sizing
Problem. 94
4.1.4 Technical Appendix for the Wagner-Whitin Algorithm. 95
4.2 Wagelmans-Hoesel-Kolen (WHK) Algorithm. 96
4.2.1 Model Formulation . 97
4.2.2 An Order T log T Algorithm for Solving Problem (4.5). 98
4.2.3 Algorithm.102
4.3 Heuristic Methods.104
4.3.1 Silver-Meal Heuristic.104
4.3.2 Least Unit Cost Heuristic .106
4.4 A Comment on the Planning Horizon.108
4.5 Exercises.109
5 Single-Period Models.113
5.1 Making Decisions in the Presence of Uncertainty.114
5.2 An Example.114
5.2.1 The Data.115
5.2.2 The Decision Model.117
Contents xv
5.3 Another Example .124
5.4 Multiple Items.127
5.4.1 A General Model.132
5.4.2 Multiple Constraints .135
5.5 Exercises .136
Inventory Planning over Multiple Time Periods: Linear-Cost Case .141
6.1 Optimal Policies .141
6.1.1 The Single-Unit, Single-Customer Approach: Single-Location
Case.142
6.1.1.1 Notation and Definitions.142
6.1.1.2 Optimality of Base-Stock Policies.145
6.1.1.3 Stochastic Lead Times.149
6.1.1.4 The Serial Systems Case.149
6.1.1.5 Generalized Demand Model.150
6.1.1.6 Capacity Limitations.151
6.2 Finding Optimal Stock Levels.151
6.2.1 Finite Planning Horizon Analysis.151
6.2.2 Constant, Positive Lead Time Case.159
6.2.3 End-of-Horizon Effects.160
6.2.4 Infinite-Horizon Analysis .161
6.2.5 Lost Sales.162
6.3 Capacity Limited Systems.163
6.3.1 The Shortfall Distribution.164
6.3.1.1 General Properties.164
6.3.2 Discrete Demand Case.166
6.3.3 An Example .171
6.4 A Serial System.173
6.4.1 An Echelon-Based Approach for Managing Inventories in
Serial Systems .174
6.4.1.1 A Decision Model.175
6.4.1.2 A Dynamic Programming Formulation of the
Decision Problem.176
6.4.1.3 An Algorithm for Computing Optimal Echelon
Stock Levels.180
6.4.1.4 Solving the Oil Rig Problem: The Stationary
Demand Case.180
6.5 Exercises .181
Contents
Background Concepts: An Introduction to the (.v ? 1. .v) Policy under
Poisson Demand.185
7.1 Steady State.186
7.1.1 Backorder Case.188
7.1.2 Lost Sales Case.190
7.2 Performance Measures.193
7.3 Properties of the Performance Measures .198
7.4 Finding Stock Levels in (s ? l,s) Policy Managed Systems:
Optimization Problem Formulations and Solution Algorithms.202
7.4.1 First Example: Minimize Expected Backorders Subject to an
Inventory Investment Constraint.202
7.4.2 Second Example: Maximize Expected System Average Fill
Rate Subject to an Inventory Investment Constraint.206
7.5 Exercises .208
A Tactical Planning Model for Managing Recoverable Items in
Multi-Echelon Systems.211
8.1 The METRIC System.212
8.1.1 System Operation and Definitions.213
8.1.2 The Optimization Problem.213
8.1.2.1 Approximating the Stationary Probability
Distribution for the Number of LRUs in Resupply. 217
8.1.2.2 Finding Depot and Base LRU Stock Levels.221
8.2 Waiting Time Analysis.230
8.3 Exercises .234
Reorder Point, Lot Size Models: The Continuous Review Case.237
9.1 An Approximate Model When Backordering Is Permitted.239
9.1.1 Assumptions.239
9.1.2 Constructing the Model.240
9.1.3 Finding Q* and r*.242
9.1.4 Convexity of the Objective Function.244
9.1.5 Lead Time Demand Is Normally Distributed .246
9.1.6 Alternative Heuristics for Computing Lot Sizes and Reorder
Points.248
9.1.7 Final Comments on the Approximate Model .253
9.2 An Exact Model .253
9.2.1 Determining the Stationary Distribution of the Inventory
Position Random Variable.254
Contents xvii
9.2.2 Determining the Stationary Distribution of the Net Inventory
Random Variable.255
9.2.3 Computing Performance Measures .256
9.2.4 Average Annual Cost Expression.258
9.2.5 Waiting Time Analysis .258
9.2.6 Continuous Approximations: The General Case.260
9.2.7 A Continuous Approximation: Normal Distribution .262
9.2.8 Another Continuous Approximation: Laplace Distribution.264
9.2.9 Optimization.266
9.2.9.1 Normal Demand Model.267
9.2.9.2 Laplace Demand Model .270
9.2.9.3 Exact Poisson Model.271
9.2.10 Additional Observations: Compound Poisson Demand
Process, Uncertain Lead Times.273
9.2.10.1 Finding the Stationary Distribution of the Inventory
Position Random Variable When an (nQ,r) Policy
Is Followed.275
9.2.10.2 Establishing the Probability Distribution of the
Inventory Position Random Variable When an (s,S)
Policy Is Employed.276
9.2.10.3 Constructing an Objective Function.278
9.2.11 Stochastic Lead Times.280
9.3 A Multi-Item Model.282
9.3.1 Model 1.283
9.3.2 Model 2.285
9.3.3 Model 3.285
9.3.4 Model 4.286
9.3.5 Finding 0,.287
9.4 Exercises .287
10 Lot Sizing Models: The Periodic Review Case.293
10.1 Notation.294
10.2 An Approximation Algorithm.296
10.2.1 Algorithm.296
10.3 Algorithm for Computing a Stationary Policy.301
10.3.1 A Primer on Dynamic Programming with an Average Cost
Criterion .302
10.3.2 Formulation and Background Results.302
10.3.3 Algorithm.307
10.4 Proof of Theorem 10.1.310
xviii Contents
10.5 A Heuristic Method for Calculating s and S.314
10.6 Exercises .316
References.319
Index.337 |
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| author | Muckstadt, John A. 1940- Sapra, Amar |
| author_GND | (DE-588)141302755 |
| author_facet | Muckstadt, John A. 1940- Sapra, Amar |
| author_role | aut aut |
| author_sort | Muckstadt, John A. 1940- |
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| ctrlnum | (OCoLC)732681798 (DE-599)BVBBV020845001 |
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| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
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| dewey-search | 658.787015118 |
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| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
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| id | DE-604.BV020845001 |
| illustrated | Illustrated |
| index_date | 2024-07-02T13:18:04Z |
| indexdate | 2024-07-09T20:26:28Z |
| institution | BVB |
| isbn | 9780387244921 9780387689487 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014166803 |
| oclc_num | 732681798 |
| open_access_boolean | |
| owner | DE-384 DE-945 DE-M347 DE-N2 DE-83 |
| owner_facet | DE-384 DE-945 DE-M347 DE-N2 DE-83 |
| physical | xviii, 339 Seiten Illustrationen |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Springer |
| record_format | marc |
| series2 | Springer Series in Operations Research and Financial Engineering |
| spelling | Muckstadt, John A. 1940- (DE-588)141302755 aut Principles of inventory management when you are down to four, order more John A. Muckstadt ; Amar Sapra Models and solutions in inventory management New York, NY [u.a.] Springer [2010] © 2010 xviii, 339 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Springer Series in Operations Research and Financial Engineering Mathematisches Modell Inventory control Inventory control Mathematical models Materialwirtschaft (DE-588)4037937-1 gnd rswk-swf Beschaffung (DE-588)4005988-1 gnd rswk-swf Lagerhaltung (DE-588)4034081-8 gnd rswk-swf Beschaffung (DE-588)4005988-1 s Lagerhaltung (DE-588)4034081-8 s DE-604 Materialwirtschaft (DE-588)4037937-1 s Sapra, Amar aut Erscheint auch als Online-Ausgabe 978-0-387-68948-7 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014166803&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Muckstadt, John A. 1940- Sapra, Amar Principles of inventory management when you are down to four, order more Mathematisches Modell Inventory control Inventory control Mathematical models Materialwirtschaft (DE-588)4037937-1 gnd Beschaffung (DE-588)4005988-1 gnd Lagerhaltung (DE-588)4034081-8 gnd |
| subject_GND | (DE-588)4037937-1 (DE-588)4005988-1 (DE-588)4034081-8 |
| title | Principles of inventory management when you are down to four, order more |
| title_alt | Models and solutions in inventory management |
| title_auth | Principles of inventory management when you are down to four, order more |
| title_exact_search | Principles of inventory management when you are down to four, order more |
| title_exact_search_txtP | Principles of inventory management when you are down to four, order more |
| title_full | Principles of inventory management when you are down to four, order more John A. Muckstadt ; Amar Sapra |
| title_fullStr | Principles of inventory management when you are down to four, order more John A. Muckstadt ; Amar Sapra |
| title_full_unstemmed | Principles of inventory management when you are down to four, order more John A. Muckstadt ; Amar Sapra |
| title_short | Principles of inventory management |
| title_sort | principles of inventory management when you are down to four order more |
| title_sub | when you are down to four, order more |
| topic | Mathematisches Modell Inventory control Inventory control Mathematical models Materialwirtschaft (DE-588)4037937-1 gnd Beschaffung (DE-588)4005988-1 gnd Lagerhaltung (DE-588)4034081-8 gnd |
| topic_facet | Mathematisches Modell Inventory control Inventory control Mathematical models Materialwirtschaft Beschaffung Lagerhaltung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014166803&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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