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An Introduction to Management Science: Quantitative Approach By: Anderson; Sweeney; Williams

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  1. Contents
  2. Preface
  3. About the Authors
  4. Chapter 1: Introduction
  5. 1.1 Problem Solving and Decision Making
  6. 1.2 Quantitative Analysis and Decision Making
  7. 1.3 Quantitative Analysis
  8. 1.4 Models of Cost, Revenue, and Profit
  9. 1.5 Management Science Techniques
  10. Summary
  11. Glossary
  12. Problems
  13. Case Problem Scheduling a Golf League
  14. Appendix 1.1 Using Excel for Breakeven Analysis
  15. Chapter 2: An Introduction to Linear Programming
  16. 2.1 A Simple Maximization Problem
  17. 2.2 Graphical Solution Procedure
  18. 2.3 Extreme Points and the Optimal Solution
  19. 2.4 Computer Solution of the Par, Inc., Problem
  20. 2.5 A Simple Minimization Problem
  21. 2.6 Special Cases
  22. 2.7 General Linear Programming Notation
  23. Summary
  24. Glossary
  25. Problems
  26. Case Problem 1 Workload Balancing
  27. Case Problem 2 Production Strategy
  28. Case Problem 3 Hart Venture Capital
  29. Appendix 2.1 Solving Linear Programs with Excel Solver
  30. Appendix 2.2 Solving Linear Programs with LINGO
  31. Chapter 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution
  32. 3.1 Introduction to Sensitivity Analysis
  33. 3.2 Graphical Sensitivity Analysis
  34. 3.3 Sensitivity Analysis: Computer Solution
  35. 3.4 Limitations of Classical Sensitivity Analysis
  36. 3.5 The Electronic Communications Problem
  37. Summary
  38. Glossary
  39. Problems
  40. Case Problem 1 Product Mix
  41. Case Problem 2 Investment Strategy
  42. Case Problem 3 Truck Leasing Strategy
  43. Appendix 3.1 Sensitivity Analysis with Excel Solver
  44. Appendix 3.2 Sensitivity Analysis with LINGO
  45. Chapter 4: Linear Programming Applications in Marketing, Finance, and Operations Management
  46. 4.1 Marketing Applications
  47. 4.2 Financial Applications
  48. 4.3 Operations Management Applications
  49. Summary
  50. Problems
  51. Case Problem 1 Planning an Advertising Campaign
  52. Case Problem 2 Schneider's Sweet Shop
  53. Case Problem 3 Textile Mill Scheduling
  54. Case Problem 4 Workforce Scheduling
  55. Case Problem 5 Duke Energy Coal Allocation
  56. Appendix 4.1 Excel Solution of Hewlitt Corporation Financial Planning Problem
  57. Chapter 5: Advanced Linear Programming Applications
  58. 5.1 Data Envelopment Analysis
  59. 5.2 Revenue Management
  60. 5.3 Portfolio Models and Asset Allocation
  61. 5.4 Game Theory
  62. Summary
  63. Glossary
  64. Problems
  65. Chapter 6: Distribution and Network Models
  66. 6.1 Supply Chain Models
  67. 6.2 Assignment Problem
  68. 6.3 Shortest-Route Problem
  69. 6.4 Maximal Flow Problem
  70. 6.5 A Production and Inventory Application
  71. Summary
  72. Glossary
  73. Problems
  74. Case Problem 1 Solutions Plus
  75. Case Problem 2 Supply Chain Design
  76. Appendix 6.1 Excel Solution of Transportation, Transshipment, and Assignment Problems
  77. Chapter 7: Integer Linear Programming
  78. 7.1 Types of Integer Linear Programming Models
  79. 7.2 Graphical and Computer Solutions for an All-Integer Linear Program
  80. 7.3 Applications Involving 0-1 Variables
  81. 7.4 Modeling Flexibility Provided by 0-1 Integer Variables
  82. Summary
  83. Glossary
  84. Problems
  85. Case Problem 1 Textbook Publishing
  86. Case Problem 2 Yeager National Bank
  87. Case Problem 3 Production Scheduling with Changeover Costs
  88. Case Problem 4 Applecore Children's Clothing
  89. Appendix 7.1 Excel Solution of Integer Linear Programs
  90. Appendix 7.2 LINGO Solution of Integer Linear Programs
  91. Chapter 8: Nonlinear Optimization Models
  92. 8.1 A Production Application-Par, Inc., Revisited
  93. 8.2 Constructing an Index Fund
  94. 8.3 Markowitz Portfolio Model
  95. 8.4 Blending: The Pooling Problem
  96. 8.5 Forecasting Adoption of a New Product
  97. Summary
  98. Glossary
  99. Problems
  100. Case Problem 1 Portfolio Optimization with Transaction Costs
  101. Case Problem 2 Cafe Compliance in the Auto Industry
  102. Appendix 8.1 Solving Nonlinear Problems with Excel Solver
  103. Appendix 8.2 Solving Nonlinear Problems with LINGO
  104. Chapter 9: Project Scheduling: PERT/CPM
  105. 9.1 Project Scheduling Based on Expected Activity Times
  106. 9.2 Project Scheduling Considering Uncertain Activity Times
  107. 9.3 Considering Time-Cost Trade-Offs
  108. Summary
  109. Glossary
  110. Problems
  111. Case Problem 1 R. C. Coleman
  112. Appendix 9.1 Finding Cumulative Probabilities for Normally Distributed Random Variables
  113. Chapter 10: Inventory Models
  114. 10.1 Economic Order Quantity (EOQ) Model
  115. 10.2 Economic Production Lot Size Model
  116. 10.3 Inventory Model with Planned Shortages
  117. 10.4 Quantity Discounts for the EOQ Model
  118. 10.5 Single-Period Inventory Model with Probabilistic Demand
  119. 10.6 Order-Quantity, Reorder Point Model with Probabilistic Demand
  120. 10.7 Periodic Review Model with Probabilistic Demand
  121. Summary
  122. Glossary
  123. Problems
  124. Case Problem 1 Wagner Fabricating Company
  125. Case Problem 2 River City Fire Department
  126. Appendix 10.1 Development of the Optimal Order Quantity (Q) Formula for the EOQ Model
  127. Appendix 10.2 Development of the Optimal Lot Size (Q*) Formula for the Production Lot Size Model
  128. Chapter 11: Waiting Line Models
  129. 11.1 Structure of a Waiting Line System
  130. 11.2 Single-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
  131. 11.3 Multiple-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
  132. 11.4 Some General Relationships for Waiting Line Models
  133. 11.5 Economic Analysis of Waiting Lines
  134. 11.6 Other Waiting Line Models
  135. 11.7 Single-Server Waiting Line Model with Poisson Arrivals and Arbitrary Service Times
  136. 11.8 Multiple-Server Model with Poisson Arrivals, Arbitrary Service Times, and No Waiting Line
  137. 11.9 Waiting Line Models with Finite Calling Populations
  138. Summary
  139. Glossary
  140. Problems
  141. Case Problem 1 Regional Airlines
  142. Case Problem 2 Office Equipment, Inc.
  143. Chapter 12: Simulation
  144. 12.1 What-If Analysis
  145. 12.2 Simulation of Sanotronics Problem
  146. 12.3 Inventory Simulation
  147. 12.4 Waiting Line Simulation
  148. 12.5 Simulation Considerations
  149. Summary
  150. Glossary
  151. Problems
  152. Case Problem 1 Four Corners
  153. Case Problem 2 Harbor Dunes Golf Course
  154. Case Problem 3 County Beverage Drive-Thru
  155. Appendix 12.1 Probability Distributions for Random Variables
  156. Appendix 12.2 Simulation with Analytic Solver
  157. Chapter 13: Decision Analysis
  158. 13.1 Problem Formulation
  159. 13.2 Decision Making without Probabilities
  160. 13.3 Decision Making with Probabilities
  161. 13.4 Risk Analysis and Sensitivity Analysis
  162. 13.5 Decision Analysis with Sample Information
  163. 13.6 Computing Branch Probabilities with Bayes' Theorem
  164. 13.7 Utility Theory
  165. Summary
  166. Glossary
  167. Problems
  168. Case Problem 1 Property Purchase Strategy
  169. Case Problem 2 Lawsuit Defense Strategy
  170. Case Problem 3 Rob's Market
  171. Case Problem 4 College Softball Recruiting
  172. Appendix 13.1 Decision Trees with Analytic Solver
  173. Chapter 14: Multicriteria Decisions
  174. 14.1 Goal Programming: Formulation and Graphical Solution
  175. 14.2 Goal Programming: Solving More Complex Problems
  176. 14.3 Scoring Models
  177. 14.4 Analytic Hierarchy Process
  178. 14.5 Establishing Priorities Using AHP
  179. 14.6 Using AHP to Develop an Overall Priority Ranking
  180. Summary
  181. Glossary
  182. Problems
  183. Case Problem 1 EZ Trailers, Inc.
  184. Appendix 14.1 Scoring Models with Excel
  185. Chapter 15: Time Series Analysis and Forecasting
  186. 15.1 Time Series Patterns
  187. 15.2 Forecast Accuracy
  188. 15.3 Moving Averages and Exponential Smoothing
  189. 15.4 Linear Trend Projection
  190. 15.5 Seasonality
  191. Summary
  192. Glossary
  193. Problems
  194. Case Problem 1 Forecasting Food and Beverage Sales
  195. Case Problem 2 Forecasting Lost Sales
  196. Appendix 15.1 Forecasting with Excel Data Analysis Tools
  197. Appendix 15.2 Using the Excel Forecast Sheet
  198. Appendices
  199. Appendix A: Building Spreadsheet Models
  200. Appendix B: Areas for the Standard Normal Distribution
  201. Appendix C: Values of e-lambda
  202. Appendix D: References and Bibliography
  203. Appendix E: Self-Test Solutions and Answers to Even-Numbered E
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[Solved] An Introduction to Management Science: Quantitative Approach By: Anderson; Sweeney; Williams

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Contents Preface About the Authors Chapter 1: Introduction 1.1 Problem Solving and Decision Making 1.2 Quantitative Analysis and Decision Making 1.3 Quantitative Analysis 1.4 Models of Cost, Revenue, and Profit 1.5 Management Science Techniques Summary Glossary Problems Case Problem Scheduling a Golf League Appendix 1.1 Using Excel for Breakeven Analysis Chapter 2: An Introduction to Linear Programming 2.1 A Simple Maximization Problem 2.2 Graphical Solution Procedure 2.3 Extreme Points and the Optimal Solution 2.4 Computer Solution of the Par, Inc., Problem 2.5 A Simple Minimization Problem 2.6 Special Cases 2.7 General Linear Programming Notation Summary Glossary Problems Case Problem 1 Workload Balancing Case Problem 2 Production Strategy Case Problem 3 Hart Venture Capital Appendix 2.1 Solving Linear Programs with Excel Solver Appendix 2.2 Solving Linear Programs with LINGO Chapter 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution 3.1 Introduction to Sensitivity Analysis 3.2 Graphical Sensitivity Analysis 3.3 Sensitivity Analysis: Computer Solution 3.4 Limitations of Classical Sensitivity Analysis 3.5 The Electronic Communications Problem Summary Glossary Problems Case Problem 1 Product Mix Case Problem 2 Investment Strategy Case Problem 3 Truck Leasing Strategy Appendix 3.1 Sensitivity Analysis with Excel Solver Appendix 3.2 Sensitivity Analysis with LINGO Chapter 4: Linear Programming Applications in Marketing, Finance, and Operations Management 4.1 Marketing Applications 4.2 Financial Applications 4.3 Operations Management Applications Summary Problems Case Problem 1 Planning an Advertising Campaign Case Problem 2 Schneider's Sweet Shop Case Problem 3 Textile Mill Scheduling Case Problem 4 Workforce Scheduling Case Problem 5 Duke Ene...
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