CHAPTER ONET Introduction 1.1 Problem Solving and Decision Making 1.2 Quantitative Analysis and Decision Making 1.3 Quantitative Analysis Model Development Data Preparation Model Solution Report Generation A Note Regarding Implementation 1.4 Models of Cost，Revenue，and Profit Cost and Volume Models Revenue and Volume Models Profit and Volume Models Break-Even Analysis 1.5 Management Science in Practice Management Science Techniques Methods Used Most Frequently Summary Glossary Problems Appendix 1.1 Spreadsheets for Management Science Appendix 1.2 The Management Scientist Software Package Management Science in Practice:Mead corporation CHAPTER TWO Linear Programming:The Graphical Method 2.1 A Simple Maximization Problem The Objective Function The Constraints Mathematical Statement of the Par，Inc.，Problem 2.2 Graphical Solution A Note on Graphing Lines Summary of the Graphical Solution Procedure for Maximization Problems Slack Variables 2.3 Extereme Points and the Optimal Solution 2.4 A Simple minimization Problem Summary of the Graphical Solution Procedure for Mixinization Problems Surplus Variables 2.5 Special Cases Alternative Optimal Solutions Infeasibility Unbounded 2.6 Introduction to Sensitivity Analysis 2.7 Graphical Sensitvity Analysis Objective Function Coefficients Right-Hand Sides Summary Glossary Problems Case Problem:Advertising Strategy Case Problem:Production Strategy CHAPTER THREE Linear Programming:Formulation，Computer Solution，and Interpretation 3.1 Computer Solution of Linear Programs Interpretation of Computer Output-A Second Example Cautionary Note on the Interpretation of Dual Prices 3.2 More Than Two Decision Variables The Modified Par，Inc.，Problem The Bluegrass Farms Problem Formulation of the Bluegrass Farms Problem Computer Solution and Interpretation for the Bluegrass Farms Problem 3.3Modeling Guidelines for Model Formulation Management Science in Action:An Optimal Wood Procurement Policy The Electronic Communications Problem Formulation of the Electronic Communications Problem Computer Solution and Interpretation for the Electronic Communications Problem Management Science in Action:Using Linear Programming for Traffic Control Summary Glossary Problems Case Problem:Product Mix Case PRoblem:Truck Leasing Strategy Appendix 3.1:Solving Linear Programs with The Management Scientist Appendix 3.2:Solving Linear Programs with LINDO/PC Appendix 3.3:Spreadsheet Solution of Linear Programs Management Science in Practice:Eastman Kodak CHAPTER FOUR Linear Programming Applications 4.1 Marketing Applications Media Selectiion Marketing Research 4.2 Financial Applications Portfolio Selection Management Science in Action:Using Linear Programming for Optimal Lease Structuring Financial Planning 4.3 Production Management Applications A Make-or-Buy Decision Production Scheduling Management Science in Action:Libbey-Owens-Ford Work-Force Assignment 4.4 Blending Problems 4.5 Data Envelopment Analysis Evaluating the Performance of Hospitals An Overview of the DEA Approach The DEA Linear Programming Model summary of the DEA Approach Summary Problems Case Problem:Environmental Protection Case Problem:Investment Strategy Case Problem:Textile Mill Scheduling Appendix 4.1 Spreadsheet Solution of Linear Programs Management Science in Practice:Marathon Oil Company CHAPTER FIVE Linear Programming:The Simplex Method 5.1 An Algebraic Overview of the Simplex Method Management Science in Action:Fleet Assignment at Delta Air Lines Algebraic Properties of the Simplex Method Determining a Basic Solution Basic Feasible Solutions 5.2 Tableau Form 5.3 Setting Up the Initial Simplex Tableau 5.4 Improving the Solution 5.5 Calculating the Next Tableau Interpreting the Results of an Iteration Moving toward a Better Solution Interpreting the Optimal Solution Summary of the Simplex Method 5.6 Tableau Form:The General Case Greater-Than-or-Equal-to Constraints Equality Constraints Eliminating Negative Right-Hand-Side Values Summary of the Steps to Create Tableau Form 5.7 Solving a Minimization Problem 5.8 Special Cases Infeasibility Unboundedness Alternative Optimal Solutions Degeneracy Summary Glossary Problems CHAPTER SIX Simplex-Based Sensitivity Analysis and Duality 6.1 Sensitivity Analysis with the Simplex Tableau Objective Function Coefficients Right-Hand-Side Values Simultaneous Changes 6.2 Duality Economic Interpretation of the Dual Variables Using the Dual to Identify the Primal Solution Finding the Dual of Any Primal Problem Summary Glossary Problems Management Science in Practice:Performance Analysis Corporation CHAPTER SEVEN Transportation，Assignment，and Transshipment Problems 7.1 The Transportation Problem:The Network Model and a Linear Programming Formulation Problem Variations A General Linear Programming Model of the Transportation Problem Management Science in Action:Marine Corps Mobilization 7.2 The Assignment Problem:The Network Model and a Linear Programming Formulation Problem Variations A General Linear Programming Model of the Assignment Problem Multiple Assignments 7.3 the Transshipment Problem:The Network Model and a Linear Programming Formulation Problem Variations A General Linear Programming Model of the Transshipment Problem 7.4 A Production and Inventory Application 7.5 The Transportation Simplex Mehtod:A Special-Purpose Solution Procedure (Optional) Phase I:Finding an Initial Feasible Solution Phase II:Iterating to the Optimal Solution Summary of the Transportation Simplex Method Problem Variations 7.6 The Assignment Problem:A Special-Purpose Solution Procedure(Optional) Finding the Minimum Number of Lines Problem Variations Summary Glossary Problems Case Problem:Assigning Umpire Crews Case Problem:Distribution System Design Management Science in Practice:Procter&Gamble CHAPTER EIGHT Integer Linear Programming Management science in Action:Scheduling Employees at McDonald’s Restaurant 8.1 Types of Integer Linear Programming Models 8.2 Graphical and computer Solution for an All-Integer Linear Program Graphical Solution Procedure Computer Solution Management Science in Action:Cutting Photographic Color Paper Rolls 8.3 Applications Capital Budgeting Models Involving Fixed Costs Distribution System Design A Bank Location Application 8.4 Modeling Flexibility Provided by 0-1 Integer Variables Multiple-choice and Mutually Exclusive Constraints Management Science in Action:Analyzing Price Quotations Under Business Volume discounts k Out of n Alternatives Constraint Conditional and Corequisite Constraints A Cautionary Note on Sensitivity Analysis Summary Glossary Problems Case Problem:Textbook Publishing Case Problem:Production Scheduling with Changeover Cosos Management Science in Practice:Ketron CHAPTER NINE Network Models 9.1 The Shortest-Route Problem A Shortest-Route Algorithm 9.2 The Minimal Spanning Tree Problem A Minimal Spanning Tree Algorithm 9.3 The Maximal Flow Problem A Maximal Flow Algorithm Summary Glossary Problems Case Problem:Ambulance Routing Management Science in Practice:EDS CHAPTER TEN Project Scheduling:PERT/CPM 10.1 Project Scheduling with Known Activity Times The Concepts of a Critical Path Dtetrmining the Critical Path Contributions of PERT/CPM Management Scince in Action:Project Management on the PC Summary of the PERT/CPM Critical Path Procedure 10.2 Project Scheduling with Uncertain Activity Times The daugherty Porta-Vac Project Uncertain Activity Times The Critical Path Variability in Project Completion Time 10.3 Considering Time-Cost Trade-Offs Crashing Activity Times A Linear Programming Model for Crashing Decisions Summary Glossary Problems Case Problem:Warehouse Expansion Management Science in Practice:Seasongood&Mayer CHAPTER ELEVEN Inventory Models 11.1 Economic Order Quantity(EOQ)Model The How-Much-to-Order Decision The When-to-Order Decision Sensitivity Analysis in the EOQ Model The Manager’s Use of the EOQ Model How Has the EOQ Decision Model Helped？ A Summary of the EOQ Model Assumptions 11.2 Economic Production Lot Size Model The Total Cost Model Finding the Economic Production Lot Size 11.3 An Inventory Model with Planned Shortages 11.4 Quantity Discounts for the EOQ Model 11.5 A Single-Period Inventory Model with Probabilistic Demand The Johnson Shoe Company Problem The Kremer Chemical Company Problem 11.6 An Order-Quantity，Reorder-Point Model with Probabilistic Demand The How-Much-to-Order Decision The When-to-Order Decision Management Science in Action:Information from a Netherlands Supplier Lowers Inventory Cost 11.7 A Periodic-Review Model with Probabilistic Demand More Complex Periodic-Review Models Management Science in Action:Inventory Model Helps Hewlett-Packard’s Product Design for Worldwide Markets 11.8 Material Requirements Planning Dependent Demand and the MRP Concept Information System for MRP MRP Calculations 11.9 The Just-in-Time Approach to Inventory Management Summary Glossary Problems Case Problem:A Make-or-Buy Analysis Appendix 11.1:Inventory Models with Spreadsheets Appendix 11.2 Development of the Optimal Order-Quantity(Q*)Formula for the EOQ Model Appendix 11.3 Development of the Optimal Lot Size(Q*)Formula for the Production Lot Size Model Appendix 11.4 Development of the Optimal Order-Quantity(Q*)and Optimal Backorder(S*)Formulas for the Planned Shortage Model Management Science in Practice:SupeRx.Inc. CHAPTER TWELVE Waiting Line Models 12.1 The Structure of a Waiting Line System The Single-Channel Waiting Line The Distribution of Arrivals The Distribution of Service Times Queue Discipine Steady-State Operation 12.2 The Single-Channel Waiting Line Model with Poisson Arrivals and Exponential Service Times The Operating Characteristics Operating Characterisitcs for the Burger Dome Problem The Manager’s Use of Waiting Line Models Improving the Waiting Line Operation 12.3 The Multiple-Channel Waiting Line Model with Poisson Arrivals and Exponential Service Times The Operating Characteristics Operating Characteristics for the Burger Dome Problem Management Science in Action:Hospital Staffing Based on a Multiple-channel Waiting Line Models 12.4 Some General Relationships for Waiting Line Models 12.5 Economic Analysis of Waiting Lines 12.6 Other Waiting Line Models 12.7 The Single-Channel Waiting Line Model with Poisson Arrivals and Arbitrary Service Times Operating Characteristics for the M/G/1 Model Constant Service Times 12.8 A Multiple-Channel Model with Poisson Arrivals，Arbitrary Service Times，and No Waiting Line The Operating Characteristics for the M/G/k Model with Blocked Customers Cleared 12.9 Waiting Line Models with Finite Calling Populations The Operating Characteristics for the M/M/1 Model with a Finite Calling Population Management Science in Action:Improving Fire Department Productivity Summary Glossary Problems Case Problem:Airline Reservations Appendix 12.1:Waiting Line Models with Spreadsheets Management Science in Practice:CITIBANK CHAPTER THIRTEEN Simulation 13.1 Using simulation for Risk Analysis The PortaCom Project The PortaCom Simulation Model Random Numbers and Simulating Values of Random Variables Using the simulation Model simulation Results Risk Analysis Conclusions Some Simulation Terminology 13.2 An Inventory Simulation Model 13.3 A Waiting Line Simulation Model The Hammondsport Svings and Loan Waiting Line Customer Arrival Times Customer Service Times The Simulation Model Simulation Results Management Science in Action:Red Cross Uses Simulation to Improve Bloodmobile Services 13.4 Ohter Issues Selecting a Simulation Language Verification and Validation Keeping Track of Time Advantages and Disadvantages Management Science in Action:Simulation at Mexico’s Vilpac Truck Company Summary Glossary Problems Case Problem:County Beverage Drive-Thru Case Problem:Machine Repair Appendix 13.1 Simulation with Spreadsheets Management Science in Practice:The Upjohn Company CHAPTER FOURTEEN Decision Analysis 14.1 Structuring the Decision Problem Payoff Tables Decision Trees 14.2 Decision Making Without Probabilities Optimistic Approach Conservative Approach Minimax Regret Approach 14.3 Decision making with Probabilities Management Science in Action:Decision Analysis and the Selection of Home Mortgages 14.4 Sensitivity Analysis 14.5 Expected Value of Perfect Information 14.6 Decisiion Analysis with Sample Information 14.7 Developing a Decision Strategy Computing Branch Probabilities An Optimal Decision Strategy Managgment Science in Action:Decision Analysis and Drug Testing for Student Athletes 14.8 Expected Value of Sample Information Efficiency of Sample Information 14.9 Utility and Decision Making The Meaning of Utility Developing Utilities for Payoffs The Expected Utility Approach Summary Glossary Problems Case Problem:Property Purchase Strategy Appendix 14.1:Decision Analysis and Spreadsheets Management Science in Practice:Ohio Edison Company CHAPTER FIFTEEN Multicriteria Decision Problems 15.1 Goal Programming:Formulation and Graphical Solution Developing the Constraints and the Goal Equations Developing and Objective Function with Preemptive Priorities The Graphical Solution Procedure The Goal Programming Model 15.2 Goal Programming:Solving More Complex Problems The Suncoast Office Supplies Problem Formulating the Goal Equations Formulating the Objective Function Computer Solution 15.3 The Analytic Hierarchy Process Management Science in Action:Using AHP and Goal Programming to Plan Facility Locations Developing the Hierarchy 15.4 Establishing Priorities Using AHP Pairwise Compaarisons The Pairwise Comparison Matrix Synthesis Procedure for Synthesizing Judgments Consistency Estimating the Consistency Ratio Other Pairwise Comparisons for the Car-Selection Problem 15.5 Using AHP to Develop an Overall Priority Ranking 15.6 Using Expert Choice to Implement AHP Summary Glossary Problems Case Problem:Production Scheduling CHAPTER SIXTEEN Forecasting 16.1 The Components of a Time Series Trend Component Cyclical Component Seasonal Component Irregular Component 16.2 Smoothing Methods Moving Averages Weighted Moving Averages Exponential Smoothing 16.3 Trend Projection 16.4 Trend and Seasonal Components The Multiplicative Model Calculating the Seasonal Indexes Deseasonalizing the Time Series using the Deseasonalized Time Series to Identify Trend Seaonal Adjustments Models Based on Monthly Data Cyclical Component 16.5 Forecasting Using Regression Models Management Science in Action:Spare Parts Forecasting at American Airlines Using Regression Analysis When Time Series Data Are Not Available Using Regression Analysis with Time Series Data 16.6 Qualitative Approaches to Forecasting Delphi Method Expert Judgment Scenario Writing Management Science in Action:The Business Week Industry Outlook Intuitive Approaches Summary Glossary Problems Case Problem:Forecasting Sales Case Problem:Forecasting Lost Sales Appendix 16.1 Forecasting with Spreadsheets Management Science in Practice:The Cincinnati Gas&Electric Company CHAPTER SEVENTEEN Markov Processes 17.1 Market Share Analysis 17.2 Accounts Receivable Analysis The Fundamental Matrix and Associated Calculations Establishing the Allowance for Doubtful Accounts Summary Glossary Problems Management Sciece in Practice:U.S.General Accounting Office CHAPTER EIGHTEEN Dynamic Programming 18.1 A Shortest-Route problem 18.2 Dynamic Programming Notation 18.3 The Knapsack Problem 18.4 A Production and Inventory Control Problem Summary Glossary Problems Management Science in Practice:The U.S.Environmental Protection Agency Appendixes A-1 A Areas for the Standard Normal Distribution B Random Digits C Values of e D Matrix Notation and Operations E References and Bibliography F Answers to Even-Numbered Problems G Solutions to Self-Test Problems
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