Introduction to management science with spreadsheets:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Boston, Mass. [u.a]
McGraw-Hill/Irwin
2006
|
| Ausgabe: | internat. ed. |
| Schriftenreihe: | The McGraw-Hill/Irwin series operations and decision sciences
|
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020021319&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XIII, 812 S. graph. Darst. 1 CD-ROM |
| ISBN: | 0071116672 |
Internformat
MARC
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| 100 | 1 | |a Stevenson, William J. |e Verfasser |0 (DE-588)13049495X |4 aut | |
| 245 | 1 | 0 | |a Introduction to management science with spreadsheets |c Bill Stevenson ; Ceyhun Ozgur |
| 250 | |a internat. ed. | ||
| 264 | 1 | |a Boston, Mass. [u.a] |b McGraw-Hill/Irwin |c 2006 | |
| 300 | |a XIII, 812 S. |b graph. Darst. |e 1 CD-ROM | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a The McGraw-Hill/Irwin series operations and decision sciences | |
| 700 | 1 | |a Ozgur, Ceyhun |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m HBZ Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020021319&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-020021319 | |
Datensatz im Suchindex
| _version_ | 1819333719472734208 |
|---|---|
| adam_text | Preface iv
WJj Part 1 Introduction to Management Science and
Forecasting 1
1 Introduction to Management Science, Modeling, and Excel
Spreadsheets 2
2 Forecasting 36
Wl Part 2 Deterministic Decision Models 102
3 Linear Programming: Basic Concepts and Graphical Solution 104
4 Applications and Solutions of Linear Programming 152
4S Linear Programming: The Simplex Method (CD-ROM ) 4S-2
5 Linear Programming: Sensitivity Analysis and Duality 206
6 Transportation, Transshipment, and Assignment Problems 274
6S Transportation and Assignment Solution Procedures
•.CD-ROM) 6S-2
7 Integer Programming 322
7S Methods of Solving Integer Programming Problems
i CD-ROM i 7S-2
8 Network Optimization Models 368
9 Nonlinear Programming 422
9S Mini Review of Differential Arithmetic CD-ROM) 9S-2
10 Multicriteria Decision-Making Models 472
ZT iats3 Probabilistic Decision Models 536
11 Decision Theory 538
12 Markov Analysis 604
13 Waiting-Line Models 658
14 Simulation 722
Appendix A: Answers to Most Odd-Numbered Problems 783
Appendix B: Tables 793
Index 799
Preface iv
[V* J Part 1 Introduction to
Management Science and
Forecasting l
1 Introduction to Management Science,
Modeling, and Excel Spreadsheets 2
Introduction 4
A Problem Focus 4
Use of a Quantitative Approach 4
Models 6
Benefits and Risks of Using Models 7
Assumptions of Models 7
Deterministic versus Probabilistic
Models 8
The Management Science Approach 9
Problem Definition 9
Model Construction 10
Model Analysis 10
Implementation and Follow-Up 11
The Utilization of Decision Support
Systems (DSS) in the Context of
Management Science 12
Plan of the Book 13
Role of Computers and Spreadsheets in
Management Science 15
Getting Started with Excel 16
Break-Even Analysis 20
Introduction to Break-Fvcn Analysis 20
Components of Break-Even Analysis 20
The Break-Even Point 24
Assumptions of Break-Even Analysis 24
Using Excel to Solve the Break-Even
Model 25
Using Excel s Goal Seek to Compute the
Break-Even Point 25
Summary of Break-Even Analysis 27
The Importance and Impact of
Management Science 27
Summary 30
Glossary 30
Discussion and Review Questions 31
Problems 32
Chapter 1 Case: Green Daisy Company 34
2 Forecasting 36
Introduction 38
Qualitative Forecasts 39
Forecasts That Use Time Series Data 39
Techniques for Averaging 41
Techniques for Trend 50
Techniques for Seasonality 59
Techniques for Cycles 64
Explanatory Models 65
Simple Linear Regression 65
Regression Assumptions 71
Multiple Regression 72
Accuracy and Control 76
Forecast Errors 77
Summarizing Forecast Accuracy 77
Monitoring and Controlling the Forecast 78
Relative Measures of Forecast Accuracy 79
Using Forecast Information 84
Selecting a Forecasting Approach 84
Summary 86
Glossary 87
Discussion and Review Questions 88
Solved Problems 89
Problems 91
Chapter 2 Case: Gnomial Functions, Inc. 100
(KLi Deterministic Decision
Models 102
3 Linear Programming: Basic Concepts and
Graphical Solution 104
Introduction 106
Constrained Optimization 106
Linear Programming 106
A Simple Example 107
Successful Implementation of Linear
Programming 108
Components and Assumptions of
LP Models 109
Formulating LP Models 112
Graphical Method 115
Graphing the Model 115
Plotting the Constrain ts 115
Finding the Optimal Solution 119
The Extreme Point Approach 119
The Objective Function (Iso-Profit Line)
Approach 122
A Minimization Example 126
Slack and Surplus 129
Some Special Issues 131
No Feasible Solutions 131
Unbounded Problems 132
Redundant Constraints 133
Multiple Optimal Solutions 134
Summary 134
Glossary 135
Solved Problems 136
Discussion and Review Questions 141
Problems 142
Chapter 3 Case: Son, Ltd. 150
4 Applications and Solutions of Linear
Programming 152
Introduction 154
Product-Mix Problems 154
Problem Formulation 155
Excel Solution of the Style and Comfort
Furniture Company Example 157
Diet Problems 163
Blending Problems 164
Marketing Applications 168
Media Selection 168
Marketing Research 172
Financial Applications 176
Financial Planning Problems for Banks 176
Portfolio Selection 179
Production Applications 180
Multiperiod Production Scheduling 181
Workforce Scheduling 183
Make-or-Buy Decisions 185
Agriculture Applications 186
Data Envelopment Analysis 189
Comment about the Use of Excel 192
Other Applications 192
Summary 193
Glossary 194
Solved Problems 195
Discussion and Review Questions 196
Problems 196
Chapter 4 Case: Direct Marketing 204
4S Linear Programming: The Simplex
Method (CD-ROM) 4S-2
Overview of the Simplex Method 4S-4
Finding an Initial Feasible Solution 4S-6
Developing the Initial Simplex Tableau 4S-7
Interpreting the Solution 4S-9
Developing the Second Tableau 4S-10
Interpreting the Second Tableau 4S-16
Developing the Third Tableau 4S-16
Interpreting the Third Tableau 4S-19
Summary of the Simplex Procedure for a
Maximization Problem 4S-20
Mixed Constraints 4S-21
= and Constraints 4S-21
Solving Maximization Problems That Have
Mixed Constraints 4S-23
Solving Minimization Problems 4S-29
Some Special Issues 4S-32
Unbounded Solutions 4S-32
Degeneracy 4S-33
Multiple Optimal Solutions 4S-34
Infeasibility 4S-35
Summary 4S-36
Glossary 4S-37
Solved Problems 4S-38
Discussion and Review Questions 4S-45
Problems 4S-46
5 Linear Programming: Sensitivity
Analysis and Duality 206
Introduction to Sensitivity Analysis 208
A Change in the Value of an Objective
Function Coefficient 209
A Change in the RHS Value of a
Constraint 213
Minimization Problems 219
Sensitivity Analysis with Excel 219
Multiple Changes 224
Summary of Sensitivity Analysis 226
Duality 226
Formulating the Dual 227
Formulating the Dual When the
Primal Has Mixed Constraints 229
Comparison of the Primal and Dual
Solutions 231
Economic Interpretation of the Dual 231
Adding Another Variable 232
Computational Considerations 232
Summary 236
Glossary 237
Solved Problems 238
Discussion and Review Questions 246
Problems 246
Chapter 5 Case: Red Brand Canners 270
6 Transportation, Transshipment, and
Assignment Problems 274
Introduction 276
Transportation Problems 276
Formulating the Model 276
Special Cases of Transportation
Problems 279
Solving Transportation Problems
Using Excel 280
Other Applications 287
Transshipment Problems 287
Aggregate Planning 294
Location Analysis 297
Assignment Problems 298
Linear Programming Formulation
of the Assignment Problem 299
Solving the Assignment Problem
Using Excel 300
Summary 303
Glossary 303
Solved Problems 303
Discussion and Review Questions 309
Problems 310
Chapter 6 Case: Sunshine Tomato Inc. 321
6S Transportation and Assignment Solution
Procedures (CD-ROM i 6S-2
Transportation Problems 6S-4
Formulating the Model 6S-4
Solution of the Transportation Model 6S-4
Overview of the Solution Technique 6S-6
Finding an Initial Feasible Solution 6S-6
Finding an Initial Feasible Solution:
The Northwest-Corner Method 6S-7
Finding an Initial Feasible Solution:
The Intuitive Approach 6S-8
Finding an Initial Feasible Solution:
VogeVs Approximation Method 6S-11
Evaluating a Solution for
Optimality 6S-13
Evaluation Using the Stepping-Stone
Method 6S-13
Evaluation Using the MODI Method 6S-16
Developing an Improved Solution 6S-18
Special Issues 6S-20
Assignment Problems 6S-24
The Hungarian Method 6S-25
Summary of Procedure 6S-29
Requirements for Use of the Hungarian
Method 6S-29
Special Situations 6S-29
Summary 6S-32
Glossary 6S-32
Solved Problems 6S-33
Discussion and Review Questions 6S-42
Problems 6S-43
7 Integer Programming 322
Introduction to Integer Programming 324
Types of Integer Programming Problems 324
Pure-Integer Problems 324
Mixed-Integer Problems 324
0-1 Integer Problems 324
Graphical Representation of Integer
Programming Problems 325
Solving Integer Programming Problems
Using Excel 326
A Comment about Sensitivity 329
Formulating Integer Programming
Problems with 0-1 Constraints 329
Either-Or Alternatives 330
k-Out-of-n Alternatives 330
If-Then Alternatives 330
Either-Or Constraints 331
Variables That Have Minimum Level
Requirements 331
Specialized Integer Programming Problems 332
Fixed-Charge Problem 333
Set Covering Problem 336
Knapsack Problem 340
Facility Location Problem 341
Traveling Salesperson Problem 344
Difficulties in Solving Integer
Programming Problems 349
Summary 351
Glossary 351
Solved Problems 352
Discussion and Review Questions 356
Problems 357
Chapter 7 Case: Suburban Suntime 365
S Methods of Solving Integer
Programming Problems (CD-ROM) 7S-2
Solving Integer Programming Problems 7S-4
The Branch and Bound Method 7S-5
A Pure-Integer Problem 7S-6
Summary of the Branch and Bound
Method for an All-Integer
Maximization Problem 7S-13
Mixed-Integer Problems 7S-14
Enumeration Method 7S-20
0-1 Problems 7S-20
Branch and Bound Method 7S-23
A Minimization Problem 7S-25
Summary 7S-26
Glossary 7S-27
Solved Problems 7S-27
Discussion and Review Questions 7S-29
Problems 7S-30
8 Network Optimization Models 368
Introduction 370
The Shortest-Route Problem 371
The Shortest-Route (Labeling) Algorithm
(Concept Development) 371
Summary of Procedure 375
Linear Programming Formulation of the
Shortest-Route Problem 376
Solving the Shortest-Route Problem
Using Excel 378
The Minimum Spanning Tree Problem 384
Algorithm for the Minimum Spanning Tree
Problem (Concept Development) 384
The Maximal Flow Problem 387
Maximal Flow Algorithm (Concept
Development) 388
Demonstration of Reverse Flow 391
Linear Programming Formulation of the
Maximal Flow Problem 393
Comment 400
Summary 401
Glossary 401
Solved Problems 401
Discussion and Review Questions 411
Problems 412
Chapter 8 Case: Furnace County Emergency
Response Routes 420
9 Nonlinear Programming 422
Introduction 424
Models with One Decision Variable 425
Unconstrained Problem with One
Decision Variable 425
Solution of One-Decision-Variable,
Unconstrained Problem with Excel 429
Constrained Problem with One
Decision Variable 433
Solution of One-Decision-Variable,
Constrained Problem with Excel 435
Models with Two Decision Variables,
Unconstrained Problem 439
Solution of Unconstrained Problems
with Two Decision Variables
Using Excel 442
Models with Two Decision Variables
and an Equality Constraint
(Lagrange Multipliers) 444
Interpreting X 446
Solution of Problems with Two Decision
Variables and a Single Equality
Constraint Using Excel 446
Models with Two Decision Variables and a
Single Inequality Constraint 449
Solution of Problems with Two
Decision Variables and Multiple
Constraints Using Excel 451
Summary 454
Glossary 456
Solved Problems 457
Discussion and Review Questions 466
Problems 466
Chapter 9 Case: Koch International
Incorporated 469
9S Mini Review of Differential Arithmetic
(CD-ROM) 9S-2
10 Multicriteria Decision-Making Models 472
Introduction 474
Goal Programming Versus Linear
Programming 474
Deviation Variables 475
Model Formulation 476
Graphical Solutions 478
Solving Goal Programming Problems
Using Excel 482
Weighted Goals 490
Analytical Hierarchy Process 493
Pairwise Comparisons 495
Normalized Pairwise Comparison
Matrix 496
Consistency Check for Criteria 496
Analytical Hierarchy Process
Using Excel 501
Scoring Models 504
The Steps for the Scoring Model 504
Summary 506
Glossary 508
Solved Problems 509
Discussion and Review Questions 523
Problems 525
Chapter 10 Case: Hi-Tech Incorporated 534
^H Part 3 Probabilistic Decision
Models 536
11 Decision Theory 538
Introduction 540
List of Alternatives 541
States of Nature 541
Payoffs 541
Degree of Certainty 541
Decision Criterion 542
The Payoff Table 542
Decision Making under Certainty 543
Decision Making under Complete
Uncertainty 544
Maximin 544
Maximax 545
Minimax Regret 545
The Hurwicz (Realism) Criterion 547
Equal Likelihood Criterion 548
Using Excel for Decision Making under
Complete Uncertainty 549
Decision Making under Risk 552
Expected Monetary Value 552
Expected Opportunity Loss 553
Expected Value of Perfect Information 553
Using Excel for Decision Making
under Risk 555
Decision Trees 556
Using TreePlan to Develop Decision
Trees with Excel 559
Sequential Decision Tree Analysis with
Excel and TreePlan 564
Decision Making with Additional
Information 567
Efficiency of Sample Information 570
Computing the Probabilities 571
Computing Revised Probabilities
with Excel 573
Sensitivity Analysis 573
Utility 578
Summary 580
Glossary 581
Solved Problems 582
Discussion and Review Questions 594
Problems 595
Chapter 11 Case: MKGP Construction
Company 602
12 Markov Analysis 604
Introduction 606
Transition Probabilities 607
System Behavior 608
Methods of Analysis 609
Tree Diagram 609
Matrix Multiplication 611
Algebraic Solution 614
Using Excel for Markov Analysis 616
Analysis of a 3 X 3 Matrix 621
Tree Diagram 622
Matrix Multiplication 623
Algebraic Solution 624
Using Excel to Solve Three-State
Problems 625
Cyclical, Transient, and Absorbing
Systems 630
Analysis of Accounts Receivable 632
Analysis of Absorbing States Using Excel 636
Assumptions 639
Summary 639
Glossary 641
Solved Problems 641
Discussion and Review Questions 649
Problems 650
Chapter 12 Case: Memorial Hospital 657
13 Waiting-Line Models 658
Introduction 660
Goals of Queuing System Design 660
Elements and Characteristics of
Waiting-Line Systems 661
Calling Population 662
Customer Arrivals 662
Poisson Distribution 663
Calculation of Poisson Probability
Using Excel 665
The Waiting Line 667
Processing Order 667
Service 667
Exponential Distribution 669
Calculation of Exponential Probability
Using Excel 672
Exit 673
Measures of System Performance 673
Basic Relationships 674
Queuing Models 676
Basic Single-Channel (M/M/l) Model 676
Basic Single-Channel Model with Poisson M
Arrival and Exponential Service Rate
(M/M/l Model) with Excel 678
Multiple-Channel Model (M/M/S) 678
Multiple-Channel Model with Poisson
Arrival and Exponential Service Rate
(M/M/S Model) with Excel 687
Determining Maximum Length of
Waiting Lines 687
Cost Considerations 690
Other Queuing Models
(Optional Coverage) 692
Model Variation I: Poisson Arrival
Rate with Any ServiceDistribution
(M/G/l) 692
Single-Channel Model with Poisson
Arrival and Any Service Distribution
(M/G/l Model) with Excel 693
Model Variation II: Poisson Arrival
Rate, Constant Service Time (MID/1) 695
Single-Channel Model with Poisson
Arrival and Constant Service
Distribution (MID/1 Model)
with Excel 695
Model Variation III: Finite
Queue Length 696
Single-Channel Model That Involves a
Finite Queue Length with Poisson
Arrival and Exponential Service
Distribution with Excel 697
Model Variation IV: Finite Calling
Population 698
Single-Channel Model That Involves a
Finite Calling Population with Poisson
Arrival and Exponential Service
Distribution with Excel 700
Model Variation V: Multiple-Server,
Priority Servicing Model 702
Revising Priorities 704
Utilization ofExcel s Goal Seek
Function 705
The Psychology of Waiting 707
The Value of Waiting Line Models 708
Summary 710
Glossary 711
Solved Problem 711
Discussion and Review Questions 713
Problems 713
Chapter 13 Case: Big Bank 721
Simulation 722
Introduction 724
Replacement Parts Illustration 725
Types of Simulation 726
Discrete versus Continuous
Simulations 726
Fixed-Interval versus Next-Event
Simulations 726
Deterministic versus Probabilistic
Simulations 111
Steps in Simulation 727
Defining the Problem and Setting
Objectives 727
Developing a Model 729
Gathering Data 729
Validating the Model 729
Designing Experiments 730
Running Simulations 730
Analyzing and Interpreting
the Results 731
The Monte Carlo Method 731
Simulation Using a Theoretical
Distribution 735
The Uniform Distribution 736
The Exponential Distribution 737
The Normal Distribution 738
Multiple-Variable Simulations 739
Computer Simulation 742
Computer Simulation Using Excel 742
Random Number Generation with
Probability Distributions
Using Excel 743
A Discrete Distribution with Two
Outcomes 746
A Discrete Distribution with More Than
Two Outcomes 747
Simulation of Waiting Lines 749
Inventory Analysis Using Simulation
and Excel Til
Scenario Manager 757
Simulation Languages 759
Pseudo-Random Numbers 760
Advantages and Limitations of
Simulation 760
When to Use Simulation 760
Summary 761
Glossary 762
Solved Problems 762
Discussion and Review Questions 769
Problems 770
Chapter 14 Case: Krohler Supermarkets 781
Appendix A: Answers to Most Odd-Numbered
Problems 783
Appendix B: Tables 793
Index 799
|
| any_adam_object | 1 |
| author | Stevenson, William J. Ozgur, Ceyhun |
| author_GND | (DE-588)13049495X |
| author_facet | Stevenson, William J. Ozgur, Ceyhun |
| author_role | aut aut |
| author_sort | Stevenson, William J. |
| author_variant | w j s wj wjs c o co |
| building | Verbundindex |
| bvnumber | BV025398637 |
| ctrlnum | (OCoLC)254755356 (DE-599)BVBBV025398637 |
| dewey-full | 658.403 658 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.403 658 |
| dewey-search | 658.403 658 |
| dewey-sort | 3658.403 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| edition | internat. ed. |
| format | Book |
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| spellingShingle | Stevenson, William J. Ozgur, Ceyhun Introduction to management science with spreadsheets |
| title | Introduction to management science with spreadsheets |
| title_auth | Introduction to management science with spreadsheets |
| title_exact_search | Introduction to management science with spreadsheets |
| title_full | Introduction to management science with spreadsheets Bill Stevenson ; Ceyhun Ozgur |
| title_fullStr | Introduction to management science with spreadsheets Bill Stevenson ; Ceyhun Ozgur |
| title_full_unstemmed | Introduction to management science with spreadsheets Bill Stevenson ; Ceyhun Ozgur |
| title_short | Introduction to management science with spreadsheets |
| title_sort | introduction to management science with spreadsheets |
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