Introduction to Operations Research 10th Edition by FREDERICK HILLIER, GERALD LIEBERMAN ISBN 0073523453 9780073523453

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ISBN 10: 0073523453 
ISBN 13: 9780073523453
Author: FREDERICK HILLIER, GERALD LIEBERMAN

Introduction to Operations Research 10th Edition Table of contents:

CHAPTER 1: Introduction

• 1.1 The Origins of Operations Research
• 1.2 The Nature of Operations Research
• 1.3 The Rise of Analytics Together with Operations Research
• 1.4 The Impact of Operations Research
• 1.5 Algorithms and OR Courseware
• Selected References
• Problems

CHAPTER 2: Overview of the Operations Research Modeling Approach

• 2.1 Defining the Problem and Gathering Data
• 2.2 Formulating a Mathematical Model
• 2.3 Deriving Solutions from the Model
• 2.4 Testing the Model
• 2.5 Preparing to Apply the Model
• 2.6 Implementation
• 2.7 Conclusions
• Selected References
• Problems

CHAPTER 3: Introduction to Linear Programming

• 3.1 Prototype Example
• 3.2 The Linear Programming Model
• 3.3 Assumptions of Linear Programming
• 3.4 Additional Examples
• 3.5 Formulating and Solving Linear Programming Models on a Spreadsheet
• 3.6 Formulating Very Large Linear Programming Models
• 3.7 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 3.1 Auto Assembly
• Case 3.2 Cutting Cafeteria Costs
• Case 3.3 Staffing a Call Center
• Case 3.4 Promoting a Breakfast Cereal

CHAPTER 4: Solving Linear Programming Problems: The Simplex Method

• 4.1 The Essence of the Simplex Method
• 4.2 Setting Up the Simplex Method
• 4.3 The Algebra of the Simplex Method
• 4.4 The Simplex Method in Tabular Form
• 4.5 Tie Breaking in the Simplex Method
• 4.6 Adapting to Other Model Forms
• 4.7 Postoptimality Analysis
• 4.8 Computer Implementation
• 4.9 The Interior-Point Approach to Solving Linear Programming Problems
• 4.10 Conclusions
• Appendix 4.1 An Introduction to Using LINDO and LINGO
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 4.1 Fabrics and Fall Fashions
• Case 4.2 New Frontiers
• Case 4.3 Assigning Students to Schools

CHAPTER 5: The Theory of the Simplex Method

• 5.1 Foundations of the Simplex Method
• 5.2 The Simplex Method in Matrix Form
• 5.3 A Fundamental Insight
• 5.4 The Revised Simplex Method
• 5.5 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems

CHAPTER 6: Duality Theory

• 6.1 The Essence of Duality Theory
• 6.2 Economic Interpretation of Duality
• 6.3 Primal–Dual Relationships
• 6.4 Adapting to Other Primal Forms
• 6.5 The Role of Duality Theory in Sensitivity Analysis
• 6.6 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems

CHAPTER 7: Linear Programming under Uncertainty

• 7.1 The Essence of Sensitivity Analysis
• 7.2 Applying Sensitivity Analysis
• 7.3 Performing Sensitivity Analysis on a Spreadsheet
• 7.4 Robust Optimization
• 7.5 Chance Constraints
• 7.6 Stochastic Programming with Recourse
• 7.7 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 7.1 Controlling Air Pollution
• Case 7.2 Farm Management
• Case 7.3 Assigning Students to Schools, Revisited
• Case 7.4 Writing a Nontechnical Memo

CHAPTER 8: Other Algorithms for Linear Programming

• 8.1 The Dual Simplex Method
• 8.2 Parametric Linear Programming
• 8.3 The Upper Bound Technique
• 8.4 An Interior-Point Algorithm
• 8.5 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems

CHAPTER 9: The Transportation and Assignment Problems

• 9.1 The Transportation Problem
• 9.2 A Streamlined Simplex Method for the Transportation Problem
• 9.3 The Assignment Problem
• 9.4 A Special Algorithm for the Assignment Problem
• 9.5 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 9.1 Shipping Wood to Market
• Case 9.2 Continuation of the Texago Case Study
• Case 9.3 Project Pickings

CHAPTER 10: Network Optimization Models

• 10.1 Prototype Example
• 10.2 The Terminology of Networks
• 10.3 The Shortest-Path Problem
• 10.4 The Minimum Spanning Tree Problem
• 10.5 The Maximum Flow Problem
• 10.6 The Minimum Cost Flow Problem
• 10.7 The Network Simplex Method
• 10.8 A Network Model for Optimizing a Project’s Time–Cost Trade-Off
• 10.9 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 10.1 Money in Motion
• Case 10.2 Aiding Allies
• Case 10.3 Steps to Success

CHAPTER 11: Dynamic Programming

• 11.1 A Prototype Example for Dynamic Programming
• 11.2 Characteristics of Dynamic Programming Problems
• 11.3 Deterministic Dynamic Programming
• 11.4 Probabilistic Dynamic Programming
• 11.5 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems

CHAPTER 12: Integer Programming

• 12.1 Prototype Example
• 12.2 Some BIP Applications
• 12.3 Innovative Uses of Binary Variables in Model Formulation
• 12.4 Some Formulation Examples
• 12.5 Some Perspectives on Solving Integer Programming Problems
• 12.6 The Branch-and-Bound Technique and Its Application to Binary Integer Programming
• 12.7 A Branch-and-Bound Algorithm for Mixed Integer Programming
• 12.8 The Branch-and-Cut Approach to Solving BIP Problems
• 12.9 The Incorporation of Constraint Programming
• 12.10 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 12.1 Capacity Concerns
• Case 12.2 Assigning Art
• Case 12.3 Stocking Sets
• Case 12.4 Assigning Students to Schools, Revisited Again

CHAPTER 13: Nonlinear Programming

• 13.1 Sample Applications
• 13.2 Graphical Illustration of Nonlinear Programming Problems
• 13.3 Types of Nonlinear Programming Problems
• 13.4 One-Variable Unconstrained Optimization
• 13.5 Multivariable Unconstrained Optimization
• 13.6 The Karush-Kuhn-Tucker (KKT) Conditions for Constrained Optimization
• 13.7 Quadratic Programming
• 13.8 Separable Programming
• 13.9 Convex Programming
• 13.10 Nonconvex Programming (with Spreadsheets)
• 13.11 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 13.1 Savvy Stock Selection
• Case 13.2 International Investments
• Case 13.3 Promoting a Breakfast Cereal, Revisited

CHAPTER 14: Metaheuristics

• 14.1 The Nature of Metaheuristics
• 14.2 Tabu Search
• 14.3 Simulated Annealing
• 14.4 Genetic Algorithms
• 14.5 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems

CHAPTER 15: Game Theory

• 15.1 The Formulation of Two-Person, Zero-Sum Games
• 15.2 Solving Simple Games—A Prototype Example
• 15.3 Games with Mixed Strategies
• 15.4 Graphical Solution Procedure
• 15.5 Solving by Linear Programming
• 15.6 Extensions
• 15.7 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems

CHAPTER 16: Decision Analysis

• 16.1 A Prototype Example
• 16.2 Decision Making without Experimentation
• 16.3 Decision Making with Experimentation
• 16.4 Decision Trees
• 16.5 Using Spreadsheets to Perform Sensitivity Analysis on Decision Trees
• 16.6 Utility Theory
• 16.7 The Practical Application of Decision Analysis
• 16.8 Conclusions
• Selected References
• Learning Aids for This Chapter on Our Website
• Problems
• Case 16.1 Brainy Business

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