9780534407759

Practical Management Science Spreadsheet Modeling and Applications (with CD-ROM Update)

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  • ISBN13:

    9780534407759

  • ISBN10:

    0534407757

  • Edition: CD
  • Format: Hardcover
  • Copyright: 5/26/2004
  • Publisher: South-Western College Pub
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Supplemental Materials

What is included with this book?

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Summary

In the Second Edition of their popular text, Wayne Winston and Chris Albright continue to build on their highly successful approach of teaching by example while using spreadsheets to model a wide variety of business problems. The authors show the relevance of topics through numerous examples of real-world implementation of management science. The ideal solution for people who want to teach by example and who want to solve real problems with spreadsheets and professional spreadsheet add-ins, this text is always interesting, in part due to the useful cases added to this edition.

Table of Contents

Introduction to Modeling
1(26)
Introduction
2(1)
A Waiting-Line Example
3(5)
Modeling versus Models
8(1)
The Seven-Step Modeling Process
8(6)
Successful Management Science Applications
14(7)
Why Study Management Science?
21(2)
Software Included in This Book
23(2)
Conclusion
25(2)
Introductory Spreadsheet Modeling
27(40)
Introduction
28(1)
Basic Spreadsheet Modeling Concepts
29(1)
Modeling Examples
30(28)
Conclusion
58(9)
Appendix Tips for Editing and Documenting Spreadsheets
62(5)
Introduction to Optimization Modeling
67(44)
Introduction
68(1)
A Brief History of Linear Programming
68(1)
Introduction to LP Modeling
69(9)
Sensitivity Analysis and the SolverTable Add-In
78(5)
The Linear Assumptions
83(3)
Graphical Solution Method
86(4)
Infeasibility and Unboundedness
90(1)
A Multiperiod Production Problem
91(7)
A Decision Support System
98(2)
Conclusion
100(11)
Appendix Information on Solvers
105(3)
Shelby Shelving
108(3)
Linear Programming Models
111(80)
Introduction
112(1)
Static Workforce Scheduling Models
113(7)
Aggregate Planning Models
120(11)
Dynamic Workforce Planning Models
131(6)
Blending Models
137(9)
Production Process Models
146(8)
Dynamic Financial Models
154(8)
Data Envelopment Analysis (DEA)
162(8)
Conclusion
170(21)
Lakefield Corporation's Oil Trading Desk
184(5)
Foreign Currency Trading
189(2)
Network Models
191(84)
Introduction
192(1)
Transportation Models
193(15)
More General Logistics Models
208(15)
Non-Logistics Network Models
223(28)
Project Scheduling Models
251(11)
Conclusion
262(13)
Optimized Motor Carrier Selection at Westvaco
271(4)
Linear Optimization Models with Integer Variables
275(62)
Introduction
276(1)
Approaches to Optimization with Integer Variables
277(1)
Capital Budgeting Models
278(12)
Fixed-Cost Models
290(10)
Lockbox Models
300(6)
Plant and Warehouse Location Models
306(7)
Set-Covering Models
313(6)
Models with Either--Or Constraints
319(4)
Cutting Stock Models
323(4)
Conclusion
327(10)
Giant Motor Company I
334(3)
Nonlinear Optimization Models
337(62)
Introduction
338(1)
Basic Ideas of Nonlinear Optimization
339(3)
Pricing Models
342(13)
Sales Force Allocation Models
355(4)
Facility Location Models
359(5)
Rating Sports Teams
364(5)
Estimating the Beta of a Stock
369(6)
Portfolio Optimization
375(17)
Conclusion
392(7)
GMS Stock Hedging
395(2)
Durham Asset Management
397(2)
Evolutionary Solver: An Alternative Optimization Procedure
399(50)
Introduction
401(2)
Introduction to Genetic Algorithms
403(2)
Introduction to the Evolutionary Solver
405(5)
Nonlinear Pricing Models
410(6)
Combinatorial Models
416(10)
Fitting an S-Shaped Curve
426(5)
Portfolio Optimization
431(2)
Cluster Analysis
433(5)
Discriminant Analysis
438(4)
Conclusion
442(7)
Assigning MBA Students to Teams
447(2)
Multi-Objective Decision Making
449(44)
Introduction
450(1)
Goal Programming
451(12)
Pareto Optimality and Trade-off Curves
463(9)
The Analytic Hierarchy Process
472(13)
Conclusion
485(8)
Play Time Toy Company
490(3)
Decision Making Under Uncertainty
493(70)
Introduction
494(2)
Elements of a Decision Analysis
496(18)
More Single-Stage Examples
514(10)
Multistage Decision Problems
524(8)
Bayes' Rule
532(8)
Incorporating Attitudes Toward Risk
540(9)
Conclusion
549(14)
GMC Motor Company II
558(2)
Jogger Shoe Company
560(1)
Westhouser Paper Company
561(2)
Introduction to Simulation Modeling
563(54)
Introduction
564(1)
Real Applications of Simulation
565(2)
Generating Uniformly Distributed Random Numbers
567(3)
Simulation with Built-In Excel Tools
570(10)
Generating Random Numbers from Other Probability Distributions
580(2)
Introduction to @Risk
582(18)
Correlation in @Risk
600(9)
Conclusion
609(8)
Ski Jacket Production
614(1)
Ebony Bath Soap
615(2)
Simulation Models
617(98)
Introduction
618(1)
Operations Models
619(25)
Financial Models
644(28)
Marketing Models
672(16)
Simulating Games of Chance
688(9)
Using TopRank with @Risk for Powerful Modeling
697(8)
Conclusion
705(10)
A College Fund Investment Decision
710(1)
Bond Investment Strategy
711(1)
Financials at Carco
712(3)
Inventory Models
715(54)
Introduction
716(1)
Categories of Inventory Models
717(2)
Types of Costs in Inventory Models
719(1)
Economic Order Quantity (EOQ) Models
720(18)
Probabilistic Inventory Models
738(9)
Ordering Simulation Models
747(6)
Supply Chain Models
753(6)
Conclusion
759(10)
Subway Token Hoarding
762(1)
Retail Pricing Using Retailer
763(6)
Queueing Models
769(54)
Introduction
770(2)
Elements of Queueing Models
772(3)
The Exponential Distribution
775(5)
Important Queueing Relationships
780(2)
Analytical Models
782(17)
Queueing Simulation
799(18)
Conclusion
817(6)
The Catalog Company Problem
821(2)
Regression Analysis
823(64)
Introduction
825(2)
Scatterplots: Graphing Relationships
827(4)
Correlations: Indicators of Linear Relationships
831(1)
Simple Linear Regression
832(7)
Multiple Regression
839(5)
The Statistical Model
844(2)
Inferences About the Regression Coefficients
846(3)
Multicollinearity
849(4)
Modeling Possibilities
853(19)
Prediction
872(2)
Conclusion
874(13)
Quantity Discounts at the FirmChair Company
882(1)
Demand for French Bread at Howie's
883(1)
Investing for Retirement
884(1)
Heating Oil at Dupree Fuels Company
885(1)
Forecasting Overhead at Wagner Printers
886(1)
Time Series Analysis and Forecasting
887(56)
Introduction
888(2)
General Concepts
890(1)
Random Series
891(7)
The Random Walk Model
898(4)
Autoregression Models
902(3)
Regression-Based Trend Models
905(7)
Moving Averages
912(5)
Exponential Smoothing
917(14)
Deseasonalizing: The Ratio-to-Moving-Averages Method
931(3)
Estimating Seasonality with Regression
934(4)
Conclusion
938(5)
Arrivals at the Credit Union
941(1)
Forecasting Weekly Sales at Amanta
942(1)
References 943(4)
Index 947

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