Quantitative analysis for business decisions:
Gespeichert in:
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| Format: | Buch |
| Sprache: | English |
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Boston, Mass. <<[u.a.]>>
Irwin
1991
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| Ausgabe: | 8. ed. |
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XX, 742 S. |
| ISBN: | 0256082677 |
Internformat
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| 245 | 1 | 0 | |a Quantitative analysis for business decisions |c Harold Bierman ; Charles P. Bonini ; Warren H. Hausman. [Ed.: Richard T. Hercher ...] |
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Datensatz im Suchindex
| _version_ | 1804138147091578880 |
|---|---|
| adam_text | Contents
part i Models and Decision Making, 1
1 Introduction to Quantitative Analysis, 3
Business Decisions, 3
Abstraction and Simplification, 4
Model Building, 5
Solutions, 5
Errors, 6
Model-Building Techniques, 6
Decisions and Uncertainty, 7
Classification of Models, 9
Simple Problems
Complex Problems
Dynamic Problems
Decision Support Systems, 11
Bibliography, 11
Problems with Answers, 12
Problems, 12
More Challenging Problems, 13
2 Introduction to Model Building, 15
Introduction, 15
x Contents
Basic Model Concepts, 15
Decision Variables
Exogenous Variables
Policies and Constraints
Performance Measures
Intermediate Variables
The Model and Relationships between Variables, 17
An Example: A Model of a Plywood Mill, 18
Relationships: The Influence Diagram
Physical Relationships
Financial Relationships
Analysis Using the Model, 22
Implementing the Model on a Computer, 24
Formulas for Other Quarters
Examples of Analysis Using the Model, 27
Sensitivity Analysis
An Example: The New York Times Model, 32
Appendix: Present Value and the Time Value of Money, 33
Bibliography, 34
Problems with Answers, 34
Problems, 35
More Challenging Problems, 36
Case 2-6: Super Spuds, Inc., 38
Case 2-7: Chase Manufacturing, 39
Case 2-8: Gotham City Times, 44
part ii Decisions Analysis, 49
3 Basic Probability Concepts, 51
Objective and Subjective Probabilities, 51
Basic Statements of Probabilities, 53
Mutually Exclusive Events, 53
Independent Events, 54
Dependent Events, 55
Conditional, Marginal, and Joint Probabilities, 55
Revision of Probabilities, 62
Random Variables, 64
The Expected Value of a Random Variable
Contents xi
Sums of Random Variables
A Constant Times a Random Variable
The Variance and Standard Deviation of a Random Variable
The Bernoulli Process and the Binomial Distribution, 69
The Binomial Probability Distribution, 71
The Binomial Probability Function, 71
Bibliography, 75
Problems with Answers, 75
Problems, 76
More Challenging Problems, 81
4 Decision Making under Uncertainty; Revision of Probabilities, 84
Conditional Value, 84
The Loss Table, 86
Expected Monetary Value, 87
Expected Opportunity Loss, 89
Expected Utility, 90
Expected Profit with Perfect Predictions, 91
Expected Value of Perfect Information, 92
Sensitivity Analysis of Subjective Probabilities, 93
Decision Trees, 95
Decision Tree for Grocer s Problem
Influence Diagram
Analysis of the Decision Problem
Developing the Decision Tree
Revision of Probabilities, 103
The Value of Imperfect Information, 104
Determining Probabilities, 107
The Value of the Survey Information, 112
Conclusion, 112
Bibliography, 113
Problems with Answers, 113
Problems, 116
More Challenging Problems, 125
Case 4-45: Department of Forests, 131
Case 4-46: Particular Motors, 133
Case 4-47: Automobile Assembly Plant, 134
Case 4-48: Telco, 136
xii Contents
5 Decision Theory, 138
The Decision Problem, 138
Decision Criteria, 140
Equally Likely
Maximax
Minimax
Maximum Likelihood
Expected Value Decision Rule
Dominance
Dominance in Decision Trees
Linear Functions, 150
The Product of Independent Random Variables, 151
Conclusion, 152
Bibliography, 153
Problems with Answers, 153
Problems, 154
More Challenging Problems, 157
6 Utility as a Basis for Decision Making, 159
Utility, 160
Measuring Utility, 161
The Psychological Assumptions, 162
Rescaling
Derivation of a Utility Function for Money, 166
The Shape of Utility Functions
Assessing a Utility Function
Using Utility Functions, 171
Certainty Equivalents
Risk Premiums
Utility Functions and Risk Preference, 174
Multiattribute Utility Functions, 176
Noncomparable Attributes: Dominance
Choice among Alternatives
Conjoint Analysis
Risky Outcomes, 181
Prospect Theory, 184
Bibliography, 186
Problems with Answers, 187
xvi Contents
13 Linear Programming: Special Topics, 397
The Transportation Problem, 397
Testing Alternate Routes
Integer Solutions
Degeneracy
Supply Not Equal to Demand
Computer Solutions
Economic Interpretations, 403
The Costs of Indirect Routes
Changes in Shipping Costs
Locational Advantages
Multiple Objectives and Goal Programming, 405
Approach 1: Single Objective with Others as Constraints
Approach 2: Define Trade-Offs among Objectives
Approach 3: Goal Programming
Approach 4: Priority Programming
Appendix: The Transportation Problem Expressed in
Conventional LP Form, 412
Bibliography, 413
Problems with Answers, 413
Problems, 415
More Challenging Problems, 417
14 Integer Programming and Branch and Bound Procedures, 421
Formulation of Integer Programming Problems, 423
The Fixed Charge Problem
Batch Size Problem
Either-Or Constraints
Examples of Integer Formulations, 425
A Capital Budgeting Problem
A Capacity Expansion Problem
Factory Size and Location
Solution of Integer Programming Problems, 431
The Branch and Bound Algorithm
The Tree of Solution Possibilities
Branch and Bound Solution of Example
Discussion
Contents xvii
Computer Solution
Discussion
Appendix: Branch and Bound Procedures for Combinatorial Problems, 444
Bibliography, 450
Problems with Answers, 451
Problems, 453
More Challenging Problems, 457
Case 14-25: Allen Company, 461
Case 14-26: Rodney Development Company, 463
part iv Deterministic and Probabilistic Models, 465
15 Inventory Control with Constant Demand, 467
ABC Analysis, 468
Performing an ABC Analysis
Cautions Regarding ABC Analysis
The Economic Order Quantity with Known Demand, 471
Sensitivity of Costs to Errors in Q
Quantity Discounts, 475
Blanket Orders
Assuming a Continuous Flow of Product, 477
Just-in-Time Inventory Systems, 478
Inventory Turnover
Appendix: Production Lot Size, 480
Bibliography, 481
Problems with Answers, 482
Problems, 482
More Challenging Problems, 484
16 Inventory Control with Reordering and Uncertain Demand, 487
Shortage Cost Model, 490
The Assumptions, 490
The Model, 490
Optimal Order Point—A Marginal Approach, 491
Computing the Standard Deviation of Lead Time Demand ( xw)
Total Expected Cost
Contents xiii
Problems, 188
More Challenging Problems, 191
7 The Normal Probability Distribution and the Value of Information, 193
Probability Distributions, 193
Cumulative Mass Functions, 195
Cumulative Distribution Functions, 196
The Normal Probability Distribution, 198
Right and Left Tails, 200
The Standardized Normal Variable and Normal Probability Tables, 201
Normal Prior Probabilities and the Value of Information, 203
Bibliography, 210
Problems with Answers, 210
Problems, 211
More Challenging Problems, 213
8 Revision of Normal Probabilities by Sampling, 216
The Probability Distributions, 217
Revising the Prior Distribution, 219
Revision of the Standard Deviation
The Posterior Normal Distribution and Decision Making, 223
The Decision to Sample, 224
The Initial Situation
The Expected Posterior Distribution
The Expected Value of Sample Information
The Sampling Decision
Optimum Sample Size, 229
A Comprehensive Example, 229
Conclusion, 234
Bibliography, 234
Problems with Answers, 235
Problems, 236
More Challenging Problems, 237
9 Game Theory, 240
Games, 240
Two-Person Zero-Sum Games, 241
Mixed Strategies, 244
xiv Contents
Graphical Solution, 245
Algebraic Solution, 248
Linear Programming Solution
Evaluation of Minimax Strategy, 250
Nonzero-Sum Games, 250
Uncertain Payoffs, 252
Competitive Bidding: The Winner s Curse, 252
Conclusions, 253
Bibliography, 254
Problems with Answers, 254
Problems, 255
More Challenging Problems, 256
part m Mathematical Programming, 259
10 Introduction to Linear Programming, 261
Formulation of Linear Programming Problems, 263
Example 1: A Product Mix Problem
Example 2: A Transportation Problem
Example 3: A Blending Problem
Example 4: A Scheduling Problem
Example 5: An Integrated Corporate Planning Model
The Art of Formulating Linear Programming Models, 273
Limitations of Linear Programming, 276
Bibliography, 277
Problems with Answers, 277
Problems, 279
More Challenging Problems, 285
Case 10-28: Impala Gold Company, 292
Case 10-29: Racy s Department Store, 293
Case 10-30: Daguscahonda Mines Company, 294
11 Solution of Linear Programming Problems, 297
Graphic Solution, 297
Sensitivity Analysis on the Constraints, 302
Dual Prices
xviii Contents
Service Level Model, 496
Other Shortage Measures
Just-in-Time Systems
Appendix: The Determination of the Optimum Order Point and
Order Size, 499
Bibliography, 502
Problems with Answers, 502
Problems, 502
More Challenging Problems, 503
17 Inventory Control with Uncertainty and No Reordering, 506
A Marginal Approach, 507
Cost of 111 Will, 510
Using a Continuous Probability Distribution, 511
Relevant Costs
Bibliography, 514
Problems with Answers, 515
Problems, 515
More Challenging Problems, 517
18 Waiting Lines: Queuing Theory, 521
Experience and Queues
Mathematical Models of Queuing, 522
A Single-Server Queuing Model, 524
Queuing System Behavior, 527
General Service Times: The M/G/l Model, 529
Constant Service Times: The MIDIX Model, 530
Role of Variability
Multiple Servers: The MlMIc Model, 532
Pooled Facilities, 535
Conclusion, 537
Appendix 1: The Poisson Process and Distribution, 538
Appendix 2: Derivation of Basic Queuing Formula, 540
Bibliography, 542
Problems with Answers, 542
Problems, 543
More Challenging Problems, 544
Contents xix
19 Simulation, 547
Probabilistic Simulation, 548
Simulation and Computers
Simulation and Inventory Control, 553
Risk Analysis, 555
Simulation with Continuous Probability Distributions, 560
Graphic Method
Computer Generation of Random Variables
Simulation of Complex Systems, 562
Appendix 1: Algebraic Method to Generate Random Variables, 564
Appendix 2: Monte Carlo Simulation on Spreadsheets, 565
Bibliography, 574
Problems with Answers, 575
Problems, 575
More Challenging Problems, 576
20 PERT: Program Evaluation and Review Technique, 580
Information Requirements
Case I: Known Activity Times, 581
Network Diagram
The Critical Path, 582
Algorithm for Critical Path
Slack and Critical Path
Time-Cost Trade-Offs, 586
Case II: Uncertain Activity Times, 591
Multiple Time Estimates for Uncertain Activity Times
Simulation of PERT Networks, 594
Evaluation of PERT, 597
Bibliography, 597
Problems with Answers, 598
Problems, 598
More Challenging Problems, 600
21 Markov Processes, 605
Short-Run Analysis
Steady-State Analysis
Calculation of Steady-State Probabilities, 610
Contents xv
Right-Hand Side (RHS) Ranges, 308
Sensitivity Analysis—New Product Evaluation, 310
Sensitivity Analysis—Objective Function Coefficients, 311
Minimization, 314
Algebraic Approach, 314
Computer Solution of Linear Programming Problems, 318
Linear Programming in Spreadsheet Packages
Parametric Programming, 322
Appendix: Interpreting LINDO Output, 327
Bibliography, 331
Problems with Answers, 331
Problems, 332
More Challenging Problems, 338
12 Linear Programming: The Simplex Method, 345
Algebraic Formulation, 345
The Simplex Method, 346
The Simplex Table
Initial Solution
Finding a New Solution
The Third Solution
Check for Optimality
Special Situations, 363
Degeneracy
Sensitivity Analysis, 366
Economic Interpretation of the C, - Z, Values
Right-Hand Side Ranges
Changes in the Prices
A Comprehensive Example, 372
Dual Prices and Reduced Costs
Addition of New Products
Right-Hand Side Ranges
Objective Function Coefficient Ranges
Appendix: Linear Programming: The Dual Problem, 381
Bibliography, 387
Problems with Answers, 387
Problems, 390
More Challenging Problems, 394
t
xx Contents
Characteristics of a Markov Process, 612
Steady-State Behavior of a Two-State Markov Process, 613
Use of Markov Processes in Decision Problems, 614
Steady-State Solution to Larger Problems, 618
Bibliography, 620
Problems with Answers, 621
Problems, 622
More Challenging Problems, 623
22 Dynamic Programming, 626
Basic Concepts, 627
Formalizing the Dynamic Programming Technique, 629
Principle of Optimality, 630
Formulation and Solution of Dynamic Programming Problems, 641
Dynamic Programming under Uncertainty, 641
Appendix: The Use of Dynamic Programming in Markov Processes, 645
Bibliography, 650
Problems with Answers, 650
Problems, 652
More Challenging Problems, 656
Appendix of Tables, 659
Table A: The Standardized Normal Distribution Function, 659
Table B: Standard Normal Distribution Loss Function, 660
Table C: Cumulative Binomial Distribution, 661
Solution to Selected Problems, 679
Index, 735
|
| adam_txt |
Contents
part i Models and Decision Making, 1
1 Introduction to Quantitative Analysis, 3
Business Decisions, 3
Abstraction and Simplification, 4
Model Building, 5
Solutions, 5
Errors, 6
Model-Building Techniques, 6
Decisions and Uncertainty, 7
Classification of Models, 9
Simple Problems
Complex Problems
Dynamic Problems
Decision Support Systems, 11
Bibliography, 11
Problems with Answers, 12
Problems, 12
More Challenging Problems, 13
2 Introduction to Model Building, 15
Introduction, 15
x Contents
Basic Model Concepts, 15
Decision Variables
Exogenous Variables
Policies and Constraints
Performance Measures
Intermediate Variables
The Model and Relationships between Variables, 17
An Example: A Model of a Plywood Mill, 18
Relationships: The Influence Diagram
Physical Relationships
Financial Relationships
Analysis Using the Model, 22
Implementing the Model on a Computer, 24
Formulas for Other Quarters
Examples of Analysis Using the Model, 27
Sensitivity Analysis
An Example: The New York Times Model, 32
Appendix: Present Value and the Time Value of Money, 33
Bibliography, 34
Problems with Answers, 34
Problems, 35
More Challenging Problems, 36
Case 2-6: Super Spuds, Inc., 38
Case 2-7: Chase Manufacturing, 39
Case 2-8: Gotham City Times, 44
part ii Decisions Analysis, 49
3 Basic Probability Concepts, 51
Objective and Subjective Probabilities, 51
Basic Statements of Probabilities, 53
Mutually Exclusive Events, 53
Independent Events, 54
Dependent Events, 55
Conditional, Marginal, and Joint Probabilities, 55
Revision of Probabilities, 62
Random Variables, 64
The Expected Value of a Random Variable
Contents xi
Sums of Random Variables
A Constant Times a Random Variable
The Variance and Standard Deviation of a Random Variable
The Bernoulli Process and the Binomial Distribution, 69
The Binomial Probability Distribution, 71
The Binomial Probability Function, 71
Bibliography, 75
Problems with Answers, 75
Problems, 76
More Challenging Problems, 81
4 Decision Making under Uncertainty; Revision of Probabilities, 84
Conditional Value, 84
The Loss Table, 86
Expected Monetary Value, 87
Expected Opportunity Loss, 89
Expected Utility, 90
Expected Profit with Perfect Predictions, 91
Expected Value of Perfect Information, 92
Sensitivity Analysis of Subjective Probabilities, 93
Decision Trees, 95
Decision Tree for Grocer's Problem
Influence Diagram
Analysis of the Decision Problem
Developing the Decision Tree
Revision of Probabilities, 103
The Value of Imperfect Information, 104
Determining Probabilities, 107
The Value of the Survey Information, 112
Conclusion, 112
Bibliography, 113
Problems with Answers, 113
Problems, 116
More Challenging Problems, 125
Case 4-45: Department of Forests, 131
Case 4-46: Particular Motors, 133
Case 4-47: Automobile Assembly Plant, 134
Case 4-48: Telco, 136
xii Contents
5 Decision Theory, 138
The Decision Problem, 138
Decision Criteria, 140
Equally Likely
Maximax
Minimax
Maximum Likelihood
Expected Value Decision Rule
Dominance
Dominance in Decision Trees
Linear Functions, 150
The Product of Independent Random Variables, 151
Conclusion, 152
Bibliography, 153
Problems with Answers, 153
Problems, 154
More Challenging Problems, 157
6 Utility as a Basis for Decision Making, 159
Utility, 160
Measuring Utility, 161
The Psychological Assumptions, 162
Rescaling
Derivation of a Utility Function for Money, 166
The Shape of Utility Functions
Assessing a Utility Function
Using Utility Functions, 171
Certainty Equivalents
Risk Premiums
Utility Functions and Risk Preference, 174
Multiattribute Utility Functions, 176
Noncomparable Attributes: Dominance
Choice among Alternatives
Conjoint Analysis
Risky Outcomes, 181
Prospect Theory, 184
Bibliography, 186
Problems with Answers, 187
xvi Contents
13 Linear Programming: Special Topics, 397
The Transportation Problem, 397
Testing Alternate Routes
Integer Solutions
Degeneracy
Supply Not Equal to Demand
Computer Solutions
Economic Interpretations, 403
The Costs of Indirect Routes
Changes in Shipping Costs
Locational Advantages
Multiple Objectives and Goal Programming, 405
Approach 1: Single Objective with Others as Constraints
Approach 2: Define Trade-Offs among Objectives
Approach 3: Goal Programming
Approach 4: Priority Programming
Appendix: The Transportation Problem Expressed in
Conventional LP Form, 412
Bibliography, 413
Problems with Answers, 413
Problems, 415
More Challenging Problems, 417
14 Integer Programming and Branch and Bound Procedures, 421
Formulation of Integer Programming Problems, 423
The Fixed Charge Problem
Batch Size Problem
Either-Or Constraints
Examples of Integer Formulations, 425
A Capital Budgeting Problem
A Capacity Expansion Problem
Factory Size and Location
Solution of Integer Programming Problems, 431
The Branch and Bound Algorithm
The Tree of Solution Possibilities
Branch and Bound Solution of Example
Discussion
Contents xvii
Computer Solution
Discussion
Appendix: Branch and Bound Procedures for Combinatorial Problems, 444
Bibliography, 450
Problems with Answers, 451
Problems, 453
More Challenging Problems, 457
Case 14-25: Allen Company, 461
Case 14-26: Rodney Development Company, 463
part iv Deterministic and Probabilistic Models, 465
15 Inventory Control with Constant Demand, 467
ABC Analysis, 468
Performing an ABC Analysis
Cautions Regarding ABC Analysis
The Economic Order Quantity with Known Demand, 471
Sensitivity of Costs to Errors in Q
Quantity Discounts, 475
Blanket Orders
Assuming a Continuous Flow of Product, 477
Just-in-Time Inventory Systems, 478
Inventory Turnover
Appendix: Production Lot Size, 480
Bibliography, 481
Problems with Answers, 482
Problems, 482
More Challenging Problems, 484
16 Inventory Control with Reordering and Uncertain Demand, 487
Shortage Cost Model, 490
The Assumptions, 490
The Model, 490
Optimal Order Point—A Marginal Approach, 491
Computing the Standard Deviation of Lead Time Demand ( xw)
Total Expected Cost
Contents xiii
Problems, 188
More Challenging Problems, 191
7 The Normal Probability Distribution and the Value of Information, 193
Probability Distributions, 193
Cumulative Mass Functions, 195
Cumulative Distribution Functions, 196
The Normal Probability Distribution, 198
Right and Left Tails, 200
The Standardized Normal Variable and Normal Probability Tables, 201
Normal Prior Probabilities and the Value of Information, 203
Bibliography, 210
Problems with Answers, 210
Problems, 211
More Challenging Problems, 213
8 Revision of Normal Probabilities by Sampling, 216
The Probability Distributions, 217
Revising the Prior Distribution, 219
Revision of the Standard Deviation
The Posterior Normal Distribution and Decision Making, 223
The Decision to Sample, 224
The Initial Situation
The Expected Posterior Distribution
The Expected Value of Sample Information
The Sampling Decision
Optimum Sample Size, 229
A Comprehensive Example, 229
Conclusion, 234
Bibliography, 234
Problems with Answers, 235
Problems, 236
More Challenging Problems, 237
9 Game Theory, 240
Games, 240
Two-Person Zero-Sum Games, 241
Mixed Strategies, 244
xiv Contents
Graphical Solution, 245
Algebraic Solution, 248
Linear Programming Solution
Evaluation of Minimax Strategy, 250
Nonzero-Sum Games, 250
Uncertain Payoffs, 252
Competitive Bidding: The Winner's Curse, 252
Conclusions, 253
Bibliography, 254
Problems with Answers, 254
Problems, 255
More Challenging Problems, 256
part m Mathematical Programming, 259
10 Introduction to Linear Programming, 261
Formulation of Linear Programming Problems, 263
Example 1: A Product Mix Problem
Example 2: A Transportation Problem
Example 3: A Blending Problem
Example 4: A Scheduling Problem
Example 5: An Integrated Corporate Planning Model
The Art of Formulating Linear Programming Models, 273
Limitations of Linear Programming, 276
Bibliography, 277
Problems with Answers, 277
Problems, 279
More Challenging Problems, 285
Case 10-28: Impala Gold Company, 292
Case 10-29: Racy's Department Store, 293
Case 10-30: Daguscahonda Mines Company, 294
11 Solution of Linear Programming Problems, 297
Graphic Solution, 297
Sensitivity Analysis on the Constraints, 302
Dual Prices
xviii Contents
Service Level Model, 496
Other Shortage Measures
Just-in-Time Systems
Appendix: The Determination of the Optimum Order Point and
Order Size, 499
Bibliography, 502
Problems with Answers, 502
Problems, 502
More Challenging Problems, 503
17 Inventory Control with Uncertainty and No Reordering, 506
A Marginal Approach, 507
Cost of 111 Will, 510
Using a Continuous Probability Distribution, 511
Relevant Costs
Bibliography, 514
Problems with Answers, 515
Problems, 515
More Challenging Problems, 517
18 Waiting Lines: Queuing Theory, 521
Experience and Queues
Mathematical Models of Queuing, 522
A Single-Server Queuing Model, 524
Queuing System Behavior, 527
General Service Times: The M/G/l Model, 529
Constant Service Times: The MIDIX Model, 530
Role of Variability
Multiple Servers: The MlMIc Model, 532
Pooled Facilities, 535
Conclusion, 537
Appendix 1: The Poisson Process and Distribution, 538
Appendix 2: Derivation of Basic Queuing Formula, 540
Bibliography, 542
Problems with Answers, 542
Problems, 543
More Challenging Problems, 544
Contents xix
19 Simulation, 547
Probabilistic Simulation, 548
Simulation and Computers
Simulation and Inventory Control, 553
Risk Analysis, 555
Simulation with Continuous Probability Distributions, 560
Graphic Method
Computer Generation of Random Variables
Simulation of Complex Systems, 562
Appendix 1: Algebraic Method to Generate Random Variables, 564
Appendix 2: Monte Carlo Simulation on Spreadsheets, 565
Bibliography, 574
Problems with Answers, 575
Problems, 575
More Challenging Problems, 576
20 PERT: Program Evaluation and Review Technique, 580
Information Requirements
Case I: Known Activity Times, 581
Network Diagram
The Critical Path, 582
Algorithm for Critical Path
Slack and Critical Path
Time-Cost Trade-Offs, 586
Case II: Uncertain Activity Times, 591
Multiple Time Estimates for Uncertain Activity Times
Simulation of PERT Networks, 594
Evaluation of PERT, 597
Bibliography, 597
Problems with Answers, 598
Problems, 598
More Challenging Problems, 600
21 Markov Processes, 605
Short-Run Analysis
Steady-State Analysis
Calculation of Steady-State Probabilities, 610
Contents xv
Right-Hand Side (RHS) Ranges, 308
Sensitivity Analysis—New Product Evaluation, 310
Sensitivity Analysis—Objective Function Coefficients, 311
Minimization, 314
Algebraic Approach, 314
Computer Solution of Linear Programming Problems, 318
Linear Programming in Spreadsheet Packages
Parametric Programming, 322
Appendix: Interpreting LINDO Output, 327
Bibliography, 331
Problems with Answers, 331
Problems, 332
More Challenging Problems, 338
12 Linear Programming: The Simplex Method, 345
Algebraic Formulation, 345
The Simplex Method, 346
The Simplex Table
Initial Solution
Finding a New Solution
The Third Solution
Check for Optimality
Special Situations, 363
Degeneracy
Sensitivity Analysis, 366
Economic Interpretation of the C, - Z, Values
Right-Hand Side Ranges
Changes in the Prices
A Comprehensive Example, 372
Dual Prices and Reduced Costs
Addition of New Products
Right-Hand Side Ranges
Objective Function Coefficient Ranges
Appendix: Linear Programming: The Dual Problem, 381
Bibliography, 387
Problems with Answers, 387
Problems, 390
More Challenging Problems, 394
t
xx Contents
Characteristics of a Markov Process, 612
Steady-State Behavior of a Two-State Markov Process, 613
Use of Markov Processes in Decision Problems, 614
Steady-State Solution to Larger Problems, 618
Bibliography, 620
Problems with Answers, 621
Problems, 622
More Challenging Problems, 623
22 Dynamic Programming, 626
Basic Concepts, 627
Formalizing the Dynamic Programming Technique, 629
Principle of Optimality, 630
Formulation and Solution of Dynamic Programming Problems, 641
Dynamic Programming under Uncertainty, 641
Appendix: The Use of Dynamic Programming in Markov Processes, 645
Bibliography, 650
Problems with Answers, 650
Problems, 652
More Challenging Problems, 656
Appendix of Tables, 659
Table A: The Standardized Normal Distribution Function, 659
Table B: Standard Normal Distribution Loss Function, 660
Table C: Cumulative Binomial Distribution, 661
Solution to Selected Problems, 679
Index, 735 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Bierman, Harold 1924- Bonini, Charles P. Hausman, Warren H. |
| author2 | Hercher, Richard T. |
| author2_role | edt |
| author2_variant | r t h rt rth |
| author_GND | (DE-588)133245861 |
| author_facet | Bierman, Harold 1924- Bonini, Charles P. Hausman, Warren H. Hercher, Richard T. |
| author_role | aut aut aut |
| author_sort | Bierman, Harold 1924- |
| author_variant | h b hb c p b cp cpb w h h wh whh |
| building | Verbundindex |
| bvnumber | BV023508000 |
| callnumber-first | H - Social Science |
| callnumber-label | HD30 |
| callnumber-raw | HD30.25.B53 1991 |
| callnumber-search | HD30.25.B53 1991 |
| callnumber-sort | HD 230.25 B53 41991 |
| callnumber-subject | HD - Industries, Land Use, Labor |
| classification_rvk | QP 327 |
| ctrlnum | (OCoLC)915806125 (DE-599)BVBBV023508000 |
| dewey-full | 658.4/03320 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.4/033 20 |
| dewey-search | 658.4/033 20 |
| dewey-sort | 3658.4 233 220 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 8. ed. |
| format | Book |
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| index_date | 2024-07-02T22:30:57Z |
| indexdate | 2024-07-09T21:23:34Z |
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| isbn | 0256082677 |
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| spelling | Bierman, Harold 1924- Verfasser (DE-588)133245861 aut Quantitative analysis for business decisions Harold Bierman ; Charles P. Bonini ; Warren H. Hausman. [Ed.: Richard T. Hercher ...] 8. ed. Boston, Mass. <<[u.a.]>> Irwin 1991 XX, 742 S. txt rdacontent n rdamedia nc rdacarrier Mathematisches Modell Industrial management -- Mathematical models Decision making -- Mathematical models Management (DE-588)4037278-9 gnd rswk-swf Entscheidungstheorie (DE-588)4138606-1 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Entscheidungsprozess (DE-588)4121202-2 gnd rswk-swf Ökonometrie (DE-588)4132280-0 gnd rswk-swf Quantitative Methode (DE-588)4232139-6 gnd rswk-swf Mathematische Methode (DE-588)4155620-3 gnd rswk-swf 1\p (DE-588)4123623-3 Lehrbuch gnd-content Operations Research (DE-588)4043586-6 s Mathematische Methode (DE-588)4155620-3 s DE-604 Entscheidungsprozess (DE-588)4121202-2 s Management (DE-588)4037278-9 s Quantitative Methode (DE-588)4232139-6 s 2\p DE-604 Entscheidungstheorie (DE-588)4138606-1 s 3\p DE-604 Ökonometrie (DE-588)4132280-0 s 4\p DE-604 Bonini, Charles P. Verfasser aut Hausman, Warren H. Verfasser aut Hercher, Richard T. edt HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016831734&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Bierman, Harold 1924- Bonini, Charles P. Hausman, Warren H. Quantitative analysis for business decisions Mathematisches Modell Industrial management -- Mathematical models Decision making -- Mathematical models Management (DE-588)4037278-9 gnd Entscheidungstheorie (DE-588)4138606-1 gnd Operations Research (DE-588)4043586-6 gnd Entscheidungsprozess (DE-588)4121202-2 gnd Ökonometrie (DE-588)4132280-0 gnd Quantitative Methode (DE-588)4232139-6 gnd Mathematische Methode (DE-588)4155620-3 gnd |
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| title | Quantitative analysis for business decisions |
| title_auth | Quantitative analysis for business decisions |
| title_exact_search | Quantitative analysis for business decisions |
| title_exact_search_txtP | Quantitative analysis for business decisions |
| title_full | Quantitative analysis for business decisions Harold Bierman ; Charles P. Bonini ; Warren H. Hausman. [Ed.: Richard T. Hercher ...] |
| title_fullStr | Quantitative analysis for business decisions Harold Bierman ; Charles P. Bonini ; Warren H. Hausman. [Ed.: Richard T. Hercher ...] |
| title_full_unstemmed | Quantitative analysis for business decisions Harold Bierman ; Charles P. Bonini ; Warren H. Hausman. [Ed.: Richard T. Hercher ...] |
| title_short | Quantitative analysis for business decisions |
| title_sort | quantitative analysis for business decisions |
| topic | Mathematisches Modell Industrial management -- Mathematical models Decision making -- Mathematical models Management (DE-588)4037278-9 gnd Entscheidungstheorie (DE-588)4138606-1 gnd Operations Research (DE-588)4043586-6 gnd Entscheidungsprozess (DE-588)4121202-2 gnd Ökonometrie (DE-588)4132280-0 gnd Quantitative Methode (DE-588)4232139-6 gnd Mathematische Methode (DE-588)4155620-3 gnd |
| topic_facet | Mathematisches Modell Industrial management -- Mathematical models Decision making -- Mathematical models Management Entscheidungstheorie Operations Research Entscheidungsprozess Ökonometrie Quantitative Methode Mathematische Methode Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016831734&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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