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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