An Introduction to Management Science Quantitative Approaches to Decision Making

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Equip students with a conceptual understanding of management science's role in the decision-making process with Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams' market-leading AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, 16E. This edition uses a hallmark problem-scenario approach in a new full-color design as the authors introduce each quantitative technique within an application setting. Students learn to apply the management science model to generate solutions and make recommendations for management. Updates clarify concept explanations while new vignettes and problems demonstrate concepts at work. Mathematical methods are presented using graphical solutions with chapter appendices that show the steps for using Microsoft® Office Excel® 365. In addition, WebAssign courseware puts techniques and models into practice with randomized problems from the book and instant feedback as well as problem walk-throughs and step-by-step tutorials.

Author(s): Jeffrey D. Camm; James J. Cochran; Michael J. Fry; Jeffrey W. Ohlmann; David R. Anderson; Dennis J. Sweeney; Thomas A. Williams
Edition: 16
Publisher: Cengage
Year: 2023

Language: English
Pages: 818

Cover
Brief Contents
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 Youth Soccer 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
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
Appendix 3.1: Sensitivity Analysis with Excel Solver
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 Planning
Case Problem 4: Workforce Scheduling
Case Problem 5: Duke Energy Coal Allocation
Appendix 4.1: Excel Solution of Hewlitt Corporation Financial Planning Problem
Chapter 5: Advanced Linear Programming Applications
5.1 Data Envelopment Analysis
5.2 Revenue Management
5.3 Portfolio Models and Asset Allocation
5.4 Game Theory
Summary
Glossary
Problems
Chapter 6: Distribution and Network Models
6.1 Supply Chain Models
6.2 Assignment Problem
6.3 Shortest-Route Problem
6.4 Maximal Flow Problem
6.5 A Production and Inventory Application
Summary
Glossary
Problems
Case Problem 1: Solutions Plus
Case Problem 2: Supply Chain Design
Appendix 6.1: Excel Solution of Transportation, Transshipment, and Assignment Problems
Chapter 7: Integer Linear Programming
7.1 Types of Integer Linear Programming Models
7.2 Graphical and Computer Solutions for an All-Integer Linear Program
7.3 Applications Involving 0-1 Variables
7.4 Modeling Flexibility Provided by 0-1 Integer Variables
Summary
Glossary
Problems
Case Problem 1: Textbook Publishing
Case Problem 2: Yeager National Bank
Case Problem 3: Production Scheduling with Changeover Costs
Case Problem 4: Applecore Children's Clothing
Appendix 7.1: Excel Solution of Integer Linear Programs
Chapter 8: Nonlinear Optimization Models
8.1 A Production Application - Par, Inc., Revisited
8.2 Constructing an Index Fund
8.3 Markowitz Portfolio Model
8.4 Blending: The Pooling Problem
8.5 Forecasting Adoption of a New Product
Summary
Glossary
Problems
Case Problem 1: Portfolio Optimization with Transaction Costs
Case Problem 2: Cafe Compliance in the Auto Industry
Appendix 8.1: Solving Nonlinear Optimization Problems with Excel Solver
Chapter 9: Project Scheduling: PERT/CPM
9.1 Project Scheduling Based on Expected Activity Times
9.2 Project Scheduling Considering Uncertain Activity Times
9.3 Considering Time-Cost Trade-Offs
Summary
Glossary
Problems
Case Problem 1: R. C. Coleman
Appendix 9.1: Finding Cumulative Probabilities for Normally Distributed Random Variables
Chapter 10: Inventory Models
10.1 Economic Order Quantity (EOQ) Model
10.2 Economic Production Lot Size Model
10.3 Inventory Model with Planned Shortages
10.4 Quantity Discounts for the EOQ Model
10.5 Single-Period Inventory Model with Probabilistic Demand
10.6 Order-Quantity, Reorder Point Model with Probabilistic Demand
10.7 Periodic Review Model with Probabilistic Demand
Summary
Glossary
Problems
Case Problem 1: Wagner Fabricating Company
Case Problem 2: River City Fire Department
Appendix 10.1: Development of the Optimal Order Quantity (Q) Formula for the EOQ Model
Appendix 10.2: Development of the Optimal Lot Size (Q*) Formula for the Production Lot Size Model
Chapter 11: Waiting Line Models
11.1 Structure of a Waiting Line System
11.2 Single-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
11.3 Multiple-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
11.4 Some General Relationships for Waiting Line Models
11.5 Economic Analysis of Waiting Lines
11.6 Kendall's Notation for Classifying Queueing Models
11.7 Single-Server Waiting Line Model with Poisson Arrivals and General Service Times
11.8 Multiple-Server Model with Poisson Arrivals, General Service Times, and No Waiting Line
11.9 Waiting Line Models with Finite Calling Populations
Summary
Glossary
Problems
Case Problem 1: Regional Airlines
Case Problem 2: Olympus Equipment, Inc.
Chapter 12: Simulation
12.1 What-If Analysis
12.2 Simulation of Sanotronics Problem
12.3 Inventory Simulation
12.4 Waiting Line Simulation
12.5 Simulation Considerations
Summary
Summary of Steps for Conducting a Simulation Analysis
Glossary
Problems
Case Problem 1: Four Corners
Case Problem 2: Harbor Dunes Golf Course
Case Problem 3: County Beverage Drive-Thru
Appendix 12.1: Common Probability Distributions for Simulation
Chapter 13: Decision Analysis
13.1 Problem Formulation
13.2 Decision Making without Probabilities
13.3 Decision Making with Probabilities
13.4 Risk Analysis and Sensitivity Analysis
13.5 Decision Analysis with Sample Information
13.6 Computing Branch Probabilities with Bayes' Theorem
13.7 Utility Theory
Summary
Glossary
Problems
Case Problem 1: Property Purchase Strategy
Case Problem 2: Lawsuit Defense Strategy
Case Problem 3: Rob's Market
Case Problem 4: College Softball Recruiting
Chapter 14: Multicriteria Decisions
14.1 Goal Programming: Formulation and Graphical Solution
14.2 Goal Programming: Solving More Complex Problems
14.3 Scoring Models
14.4 Analytic Hierarchy Process
14.5 Establishing Priorities Using AHP
14.6 Using AHP to Develop an Overall Priority Ranking
Summary
Glossary
Problems
Case Problem 1: Banh Trailers, Inc.
Appendix 14.1: Scoring Models with Excel
Chapter 15: Time Series Analysis and Forecasting
15.1 Time Series Patterns
15.2 Forecast Accuracy
15.3 Moving Averages and Exponential Smoothing
15.4 Linear Trend Projection
15.5 Seasonality
Summary
Glossary
Problems
Case Problem 1: Forecasting Food and Beverage Sales
Case Problem 2: Forecasting Lost Sales
Appendix 15.1: Forecasting with Excel Data Analysis Tools
Appendix 15.2: Using the Excel Forecast Sheet
Chapter 16: Markov Processes
16.1 Market Share Analysis
16.2 Accounts Receivable Analysis
Summary
Glossary
Problems
Case Problem 1: Dealer's Absorbing State Probabilities in Blackjack
Appendix 16.1: Matrix Notation and Operations
Appendix 16.2: Matrix Inversion with Excel
Appendices
Appendix A: Building Spreadsheet Models
Appendix B: Areas for the Standard Normal Distribution
Appendix C: Values of e-Lambda
Appendix D: References and Bibliography
Index