introduction to operations research seventh editionPDF电子书下载

CHAPTER 1 Introduction 1

1.1 The Origins of Operations Research 1

1.2 The Nature of Operations Research 2

1.3 The Impact of Operations Research 3

1.4 Algorithms and OR Courseware 5

Problems 6

CHAPTER 2 Overview of the Operations Research Modeling Approach 7

2.1 Defining the Problem and Gathering Data 7

2.2 Formulating a Mathematical Model 10

2.3 Deriving Solutions from the Model 14

2.4 Testing the Model 16

2.5 Preparing to Apply the Model 18

2.6 Implementation 20

2.7 Conclusions 21

Selected References 22

Problems 22

CHAPTER 3 Introduction to Linear Programming 24

3.1 Prototype Example 25

3.2 The Linear Programming Model 31

3.3 Assumptions of Linear Programming 36

3.4 Additional Examples 44

3.5 Some Case Studies 61

3.6 Displaying and Solving Linear Programming Models on a Spreadsheet 67

3.7 Formulating Very Large Linear Programming Models 73

3.8 Conclusions 79

Appendix 3.1 The LINGO Modeling Language 79

Selected References 89

Learning Aids for This Chapter in Your OR Courseware 90

Problems 90

Case 3.1 Auto Assembly 103

Case 3.2 Cutting Cafeteria Costs 104

Case 3.3 Staffing a Call Center 106

CHAPTER 4 Solving Linear Programming Problems：The Simplex Method 109

4.1 The Essence of the Simplex Method 109

4.2 Setting Up the Simplex Method 114

4.3 The Algebra of the Simplex Method 118

4.4 The Simplex Method in Tabular Form 123

4.5 Tie Breaking in the Simplex Method 128

4.6 Adapting to Other Model Forms 132

4.7 Postoptimality Analysis 152

4.8 Computer Implementation 160

4.9 The Interior-Point Approach to Solving Linear Programming Problems 163

4.10 Conclusions 168

Appendix 4.1 An Introduction to Using LINDO 169

Selected References 171

Learning Aids for This Chapter in Your OR Courseware 172

Problems 172

Case 4.1 Fabrics and Fall Fashions 182

Case 4.2 New Frontiers 185

Case 4.3 Assigning Students to Schools 188

CHAPTER 5 The Theory of the Simplex Method 190

5.1 Foundations of the Simplex Method 190

5.2 The Revised Simplex Method 202

5.3 A Fundamental Insight 212

5.4 Conclusions 220

Selected References 220

Learning Aids for This Chapter in Your OR Courseware 221

Problems 221

CHAPTER 6 Duality Theory and Sensitivity Analysis 230

6.1 The Essence of Duality Theory 231

6.2 Economic Interpretation of Duality 239

6.3 Primal-Dual Relationships 242

6.4 Adapting to Other Primal Forms 247

6.5 The Role of Duality Theory in Sensitivity Analysis 252

6.6 The Essence of Sensitivity Analysis 254

6.7 Applying Sensitivity Analysis 262

6.8 Conclusions 284

Selected References 284

Learning Aids for This Chapter in Your OR Courseware 285

Problems 285

Case 6.1 Controlling Air Pollution 302

Case 6.2 Farm Management 304

Case 6.3 Assigning Students to Schools（Revisited） 307

CHAPTER 7 Other Algorithms for Linear Programming 309

7.1 The Dual Simplex Method 309

7.2 Parametric Linear Programming 312

7.3 The Upper Bound Technique 317

7.4 An Interior-Point Algorithm 320

7.5 Linear Goal Programming and Its Solution Procedures 332

7.6 Conclusions 339

Selected References 340

Learning Aids for This Chapter in Your OR Courseware 340

Problems 341

Case 7.1 A Cure for Cuba 347

CHAPTER 8 The Transportation and Assignment Problems 350

8.1 The Transportation Problem 351

8.2 A Streamlined Simplex Method for the Transportation Problem 365

8.3 The Assignment Problem 381

8.4 Conclusions 391

Selected References 391

Learning Aids for This Chapter in Your OR Courseware 392

Problems 392

Case 8.1 Shipping Wood to Market 401

Case 8.2 Project Pickings 402

CHAPTER 9 Network Optimization Models 405

9.1 Prototype Example 406

9.2 The Terminology of Networks 407

9.3 The Shortest-Path Problem 411

9.4 The Minimum Spanning Tree Problem 415

9.5 The Maximum Flow Problem 420

9.6 The Minimum Cost Flow Problem 429

9.7 The Network Simplex Method 438

9.8 Conclusions 448

Selected References 449

Learning Aids for This Chapter in Your OR Courseware 449

Problems 450

Case 9.1 Aiding Allies 458

Case 9.2 Money in Motion 464

CHAPTER 10 Project Management with PERT/CPM 468

10.1 A Prototype Example—The Reliable Construction Co.Project 469

10.2 Using a Network to Visually Display a Project 470

10.3 Scheduling a Project with PERT/CPM 475

10.4 Dealing with Uncertain Activity Durations 485

10.5 Considering Time-Cost Trade-Offs 492

10.6 Scheduling and Controlling Project Costs 502

10.7 An Evaluation of PERT/CPM 508

10.8 Conclusions 512

Selected References 513

Learning Aids for This Chapter in Your OR Courseware 514

Problems 514

Case 10.1 Steps to Success 524

Case 10.2 “School’s out forever！！” 527

CHAPTER 11 Dynamic Programming 533

11.1 A Prototype Example for Dynamic Programming 533

11.2 Characteristics of Dynamic Programming Problems 538

11.3 Deterministic Dynamic Programming 541

11.4 Probabilistic Dynamic Programming 562

11.5 Conclusions 568

Selected References 568

Learning Aids for This Chapter in Your OR Courseware 568

Problems 569

CHAPTER 12Integer Programming 576

12.1 Prototype Example 577

12.2 Some BIP Applications 580

12.3 Innovative Uses of Binary Variables in Model Formulation 585

12.4 Some Formulation Examples 591

12.5 Some Perspectives on Solving Integer Programming Problems 600

12.6 The Branch-and-Bound Technique and Its Application to Binary Integer Programming 604

12.7 A Branch-and-Bound Algorithm for Mixed Integer Programming 616

12.8 Other Developments in Solving BIP Problems 622

12.9 Conclusions 630

Selected References 631

Learning Aids for This Chapter in Your OR Courseware 631

Problems 632

Case 12.1 Capacity Concerns 642

Case 12.2 Assigning Art 645

Case 12.3 Stocking Sets 649

Case 12.4 Assigning Students to Schools（Revisited Again） 653

CHAPTER 13 Nonlinear Programming 654

13.1 Sample Applications 655

13.2 Graphical Illustration of Nonlinear Programming Problems 659

13.3 Types of Nonlinear Programming Problems 664

13.4 One-Variable Unconstrained Optimization 670

13.5 Multivariable Unconstrained Optimization 673

13.6 The Karush-Kuhn-Tucker （KKT） Conditions for Constrained Optimization 679

13.7 Quadratic Programming 683

13.8 Separable Programming 690

13.9 Convex Programming 697

13.10 Nonconvex Programming 702

13.11 Conclusions 706

Selected References 706

Learning Aids for This Chapter in Your OR Courseware 707

Problems 708

Case 13.1 Savvy Stock Selection 720

CHAPTER 14 Game Theory 726

14.1 The Formulation of Two-Person，Zero-Sum Games 726

14.2 Solving Simple Games—A Prototype Example 728

14.3 Games with Mixed Strategies 733

14.4 Graphical Solution Procedure 735

14.5 Solving by Linear Programming 738

14.6 Extensions 741

14.7 Conclusions 742

Selected References 743

Learning Aids for This Chapter in Your OR Courseware 743

Problems 743

CHAPTER 15 Decision Analysis 749

15.1 A Prototype Example 750

15.2 Decision Making without Experimentation 751

15.3 Decision Making with Experimentation 758

15.4 Decision Trees 764

15.5 Utility Theory 770

15.6 The Practical Application of Decision Analysis 778

15.7 Conclusions 781

Selected References 781

Learning Aids for This Chapter in Your OR Courseware 782

Problems 782

Case 15.1 Brainy Business 795

Case 15.2 Smart Steering Support 798

CHAPTER 16 Markov Chains 802

16.1 Stochastic Processes 802

16.2 Markov Chains 803

16.3 Chapman-Kolmogorov Equations 808

16.4 Classification of States of a Markov Chain 810

16.5 Long-Run Properties of Markov Chains 812

16.6 First Passage Times 818

16.7 Absorbing States 820

16.8 Continuous Time Markov Chains 822

Selected References 827

Learning Aids for This Chapter in Your OR Courseware 828

Problems 828

CHAPTER 17 Queueing Theory 834

17.1 Prototype Example 835

17.2 Basic Structure of Queueing Models 835

17.3 Examples of Real Queueing Systems 840

17.4 The Role of the Exponential Distribution 841

17.5 The Birth-and-Death Process 848

17.6 Queueing Models Based on the Birth-and-Death Process 852

17.7 Queueing Models Involving Nonexponential Distributions 871

17.8 Priority-Discipline Queueing Models 879

17.9 Queueing Networks 885

17.10 Conclusions 889

Selected References 890

Learning Aids for This Chapter in Your OR Courseware 890

Problems 891

Case 17.1 Reducing In-Process Inventory 905

CHAPTER 18 The Application of Queueing Theory 907

18.1 Examples 907

18.2 Decision Making 909

18.3 Formulation of Waiting-Cost Functions 912

18.4 Decision Models 917

18.5 Some Award-Winning Applications of Queueing Theory 923

18.6 Conclusions 926

Selected References 926

Learning Aids for This Chapter in Your OR Courseware 926

Problems 927

Case 18.1 Queueing Quandary 932

CHAPTER 19 Inventory Theory 935

19.1 Examples 936

19.2 Components of Inventory Models 938

19.3 Deterministic Continuous-Review Models 941

19.4 A Deterministic Periodic-Review Model 951

19.5 A Stochastic Continuous-Review Model 956

19.6 A Stochastic Single-Period Model for Perishable Products 961

19.7 Stochastic Periodic-Review Models 975

19.8 Larger Inventory Systems in Practice 983

19.9 Conclusions 987

Selected References 987

Learning Aids for This Chapter in Your OR Courseware 987

Problems 988

Case 19.1 Brushing Up on Inventory Control 1000

Case 19.2 TNT：Tackling Newsboy’s Teachings 1002

Case 19.3 Jettisoning Surplus Stock 1004

CHAPTER 20 Forecasting 1009

20.1 Some Applications of Forecasting 1010

20.2 Judgmental Forecasting Methods 1013

20.3 Time Series 1014

20.4 Forecasting Methods for a Constant-Level Model 1016

20.5 Incorporating Seasonal Effects into Forecasting Methods 1018

20.6 An Exponential Smoothing Method for a Linear Trend Model 1021

20.7 Forecasting Errors 1025

20.8 Box-Jenkins Method 1026

20.9 Causal Forecasting with Linear Regression 1028

20.10 Forecasting in Practice 1036

20.11 Conclusions 1038

Selected References 1038

Learning Aids for This Chapter in Your OR Courseware 1038

Problems 1039

Case 20.1 Finagling the Forecasts 1048

CHAPTER 21 Markov Decision Processes 1053

21.1 A Prototype Example 1053

21.2 A Model for Markov Decision Processes 1056

21.3 Linear Programming and Optimal Policies 1059

21.4 Policy Improvement Algorithm for Finding Optimal Policies 1064

21.5 Discounted Cost Criterion 1069

Selected References 1077

Learning Aids for This Chapter in Your OR Courseware 1078

Problems 1078

CHAPTER 22 Simulation 1084

22.1 The Essence of Simulation 1084

22.2 Some Common Types of Applications of Simulation 1097

22.3 Generation of Random Numbers 1101

22.4 Generation of Random Observations from a Probability Distribution 1105

22.5 Outline of a Major Simulation Study 1110

22.6 Performing Simulations on Spreadsheets 1115

22.7 Variance-Reducing Techniques 1126

22.8 Regenerative Method of Statistical Analysis 1131

22.9 Conclusions 1138

Selected References 1140

Learning Aids for This Chapter in Your OR Courseware 1140

Problems 1141

Case 22.1 Planning Planers 1151

Case 22.2 Pricing under Pressure 1153

APPENDIXES 1156

1.Documentation for the OR Courseware 1156

2.Convexity 1159

3.Classical Optimization Methods 1165

4.Matrices and Matrix Operations 1169

5.Tables 1174

PARTIAL ANSWERS TO SELECTED PROBLEMS 1176

INDEXES 1195

Author Index 1195

Subject Index 1199