A practical introduction to management science:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Harlow <<[u.a.]>>
Addison-Wesley
1998
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. 563 - 565 |
| Beschreibung: | XII, 572 S. zahlr. graph. Darst. |
| ISBN: | 0201178478 |
Internformat
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents
Preface x
Chapter 1
Introducing management science 1
Chapter outline 1
1.1 What is management science? 2
1.2 Management science methods 8
Chapter review 15
Key terms ] 5
Case study: Perran Downs Pre-School Education Centre 16
Problems 15
Discussion questions 17
Chapter 2
Financial models 18
Chapter outline 18
2.1 Break-even point 19
2.2 Value of money over time 27
2.3 Replacing equipment 37
2.4 Scoring models 47
Chapter review 50
Key terms 50
Case study: Manning-Gaumont pic 51
Problems 52
Discussion questions 54
Chapter 3
Linear programming 55
Chapter outline 55
3.1 Introduction 56
3.2 Formulating linear programmes 57
3.3 Using graphs to solve linear programmes 66
3.4 Sensitivity analysis 73
3.5 Solving real problems 81
Chapter review 90
Key terms 90
Case study: Smithers Engineering Company 91
Problems 93
Discussion questions 95
v
I vi | CONTENTS
Chapter 4
Extensions to linear programming 99
Chapter outline 99
4.1 Integer linear programming 100
4.2 Zero-one programming 113
4.3 Goal programming 119
4.4 Dynamic programming 127
Chapter review 135
Key terms 135
Case study: Alberta Research Council 136
Problems 137
Discussion questions 140
Chapter 5
Scheduling and routing 141
Chapter outline 141
5.1 Background to scheduling 142
5.2 Scheduling jobs on machines 146
5.3 The Assignment Problem 156
5.4 The Transportation Problem 164
5.5 Shortest paths through a network 177
5.6 Maximum flow through a network 184
Chapter review 192
Key terms 192
Case study: International Electronic Trading Corporation 193
Problems 197
Discussion questions 200
Chapter 6
Forecasting 201
Chapter outline 201
6.1 Forecasting within an organization 202
6.2 Judgemental forecasting 206
6.3 Time series and forecast errors 209
6.4 Causal forecasting 215
6.5 Projective forecasting 227
Chapter review 248
Key terms 248
Case study: Loch Erichsae Knitwear Company 249
Problems 252
Discussion questions 254
CONTENTS | vii
Chapter 7
Probability and probability distributions 255
Chapter outline 255
7.1 Describing data 256
7.2 Measures for average and spread 257
7.3 Probability 264
7.4 Calculating probabilities for independent events 265
7.5 Conditional probabilities for dependent events 270
7.6 Probability distributions 278
7.7 Binomial distribution 280
7.8 Poisson distribution 286
7.9 Normal distribution 293
Chapter review 303
Key terms 303
Case study: The Gamblers Press 303
Problems 305
Discussion questions 308
Chapter 8
Statistical sampling and testing 309
Chapter outline 309
8.1 Reliability and replacement 310
8.2 Sampling 324
8.3 Hypothesis testing 334
Chapter review 345
Key terms 345
Case study: Willingham Consumer Protection Department 346
Problems 347
Discussion questions 348
Chapter 9
Decision analysis 350
Chapter outline 350
9.1 Giving structure to decisions 35 ]
9.2 Decision-making under certainty 353
9.3 Decision-making under uncertainty 355
9.4 Decision-making under risk 368
9.5 Sequential decisions and decision trees 378
Chapter review 385
Key terms 385
Case study: John Sparrow s petrol additive 386
Problems 388
Discussion questions 391
viii | CONTENTS
Chapter 10
Project management 392
Chapter outline 392
10.1 Background to project management 393
10.2 Project networks 396
10.3 Timing of projects 408
10.4 Programme evaluation and review technique 418
10.5 Changing project times 424
10.6 Gantt charts and resource levelling 433
Chapter review 439
Key terms 439
Case study: Accime Products 440
Problems 442
Discussion questio 446
Chapter 11
Inventory control 447
Chapter outline 447
11.1 Background to stock control 448
11.2 Fixed order quantities 455
11.3 Production systems 466
11.4 Uncertain demand 471
11.5 Single period models 479
11.6 ABC analysis of inventories 481
11.7 Dependent demand inventory systems 484
Chapter review 495
Key terms 495
Case study: The Midland Pill Supply Company 496
Problems 498
Discussion questions 500
CONTENTS | ix
Chapter 12
Simulation and queues 501
Chapter outline 501
12.1 Queues at single servers 502
12.2 Multi-server queues 509
12.3 Simulation methods 515
12.4 Random sampling 521
12.5 Simulation flow charts 530
12.6 Benefits of simulation 540
Chapter review 542
Key terms 543
Case study: City Assistance 543
Problems 546
Discussion questions 547
Appendix A
Solutions to self-assessment questions 548
Appendix B
Probabilities for the binomial distribution 554
Appendix C
Probabilities for the Poisson distribution 559
Appendix D
Probabilities for the normal distribution 562
Appendix E
Selected references 563
Index 566
|
| adam_txt |
Contents
Preface x
Chapter 1
Introducing management science 1
Chapter outline 1
1.1 What is management science? 2
1.2 Management science methods 8
Chapter review 15
Key terms ] 5
Case study: Perran Downs Pre-School Education Centre 16
Problems 15
Discussion questions 17
Chapter 2
Financial models 18
Chapter outline 18
2.1 Break-even point 19
2.2 Value of money over time 27
2.3 Replacing equipment 37
2.4 Scoring models 47
Chapter review 50
Key terms 50
Case study: Manning-Gaumont pic 51
Problems 52
Discussion questions 54
Chapter 3
Linear programming 55
Chapter outline 55
3.1 Introduction 56
3.2 Formulating linear programmes 57
3.3 Using graphs to solve linear programmes 66
3.4 Sensitivity analysis 73
3.5 Solving real problems 81
Chapter review 90
Key terms 90
Case study: Smithers Engineering Company 91
Problems 93
Discussion questions 95
v
I vi | CONTENTS
Chapter 4
Extensions to linear programming 99
Chapter outline 99
4.1 Integer linear programming 100
4.2 Zero-one programming 113
4.3 Goal programming 119
4.4 Dynamic programming 127
Chapter review 135
Key terms 135
Case study: Alberta Research Council 136
Problems 137
Discussion questions 140
Chapter 5
Scheduling and routing 141
Chapter outline 141
5.1 Background to scheduling 142
5.2 Scheduling jobs on machines 146
5.3 The Assignment Problem 156
5.4 The Transportation Problem 164
5.5 Shortest paths through a network 177
5.6 Maximum flow through a network 184
Chapter review 192
Key terms 192
Case study: International Electronic Trading Corporation 193
Problems 197
Discussion questions 200
Chapter 6
Forecasting 201
Chapter outline 201
6.1 Forecasting within an organization 202
6.2 Judgemental forecasting 206
6.3 Time series and forecast errors 209
6.4 Causal forecasting 215
6.5 Projective forecasting 227
Chapter review 248
Key terms 248
Case study: Loch Erichsae Knitwear Company 249
Problems 252
Discussion questions 254
CONTENTS | vii
Chapter 7
Probability and probability distributions 255
Chapter outline 255
7.1 Describing data 256
7.2 Measures for average and spread 257
7.3 Probability 264
7.4 Calculating probabilities for independent events 265
7.5 Conditional probabilities for dependent events 270
7.6 Probability distributions 278
7.7 Binomial distribution 280
7.8 Poisson distribution 286
7.9 Normal distribution 293
Chapter review 303
Key terms 303
Case study: The Gamblers' Press 303
Problems 305
Discussion questions 308
Chapter 8
Statistical sampling and testing 309
Chapter outline 309
8.1 Reliability and replacement 310
8.2 Sampling 324
8.3 Hypothesis testing 334
Chapter review 345
Key terms 345
Case study: Willingham Consumer Protection Department 346
Problems 347
Discussion questions 348
Chapter 9
Decision analysis 350
Chapter outline 350
9.1 Giving structure to decisions 35 ]
9.2 Decision-making under certainty 353
9.3 Decision-making under uncertainty 355
9.4 Decision-making under risk 368
9.5 Sequential decisions and decision trees 378
Chapter review 385
Key terms 385
Case study: John Sparrow's petrol additive 386
Problems 388
Discussion questions 391
viii | CONTENTS
Chapter 10
Project management 392
Chapter outline 392
10.1 Background to project management 393
10.2 Project networks 396
10.3 Timing of projects 408
10.4 Programme evaluation and review technique 418
10.5 Changing project times 424
10.6 Gantt charts and resource levelling 433
Chapter review 439
Key terms 439
Case study: Accime Products 440
Problems 442
Discussion questio 446
Chapter 11
Inventory control 447
Chapter outline 447
11.1 Background to stock control 448
11.2 Fixed order quantities 455
11.3 Production systems 466
11.4 Uncertain demand 471
11.5 Single period models 479
11.6 ABC analysis of inventories 481
11.7 Dependent demand inventory systems 484
Chapter review 495
Key terms 495
Case study: The Midland Pill Supply Company 496
Problems 498
Discussion questions 500
CONTENTS | ix
Chapter 12
Simulation and queues 501
Chapter outline 501
12.1 Queues at single servers 502
12.2 Multi-server queues 509
12.3 Simulation methods 515
12.4 Random sampling 521
12.5 Simulation flow charts 530
12.6 Benefits of simulation 540
Chapter review 542
Key terms 543
Case study: City Assistance 543
Problems 546
Discussion questions 547
Appendix A
Solutions to self-assessment questions 548
Appendix B
Probabilities for the binomial distribution 554
Appendix C
Probabilities for the Poisson distribution 559
Appendix D
Probabilities for the normal distribution 562
Appendix E
Selected references 563
Index 566 |
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| title | A practical introduction to management science |
| title_auth | A practical introduction to management science |
| title_exact_search | A practical introduction to management science |
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| title_full | A practical introduction to management science Donald Waters |
| title_fullStr | A practical introduction to management science Donald Waters |
| title_full_unstemmed | A practical introduction to management science Donald Waters |
| title_short | A practical introduction to management science |
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