An Introduction to Management Science: Quantitative Approaches to Decision Making 15th edition

Textbook Cover

David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, and Jeffrey W. Ohlmann
Publisher: Cengage Learning

enhanced content

Cengage Unlimited

Included in a Cengage Unlimited subscription. Learn More

eBook

eBook

Your students can pay an additional fee for access to an online version of the textbook that might contain additional interactive features.

lifetime of edition

Lifetime of Edition (LOE)

Your students are allowed unlimited access to WebAssign courses that use this edition of the textbook at no additional cost.

course pack

Course Packs

Save time with ready-to-use assignments built by subject matter experts specifically for this textbook. You can customize and schedule any of the assignments you want to use.

textbook resources

Textbook Resources

Additional instructional and learning resources are available with the textbook, and might include testbanks, slide presentations, online simulations, videos, and documents.


  • Anderson Introduction to Management Science: Quantitative Approaches to Decision Making 15e

Access is contingent on use of this textbook in the instructor's classroom.

Academic Term Homework and eBook
Higher Education Single Term $135.00
Higher Education Multi-Term $145.00
High School $10.50

Online price per student per course or lab, bookstore price varies. Access cards can be packaged with most any textbook, please see your textbook rep or contact WebAssign

  • 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
    • 1: Exercises (13)
    • 1: Case Problems
    • 1: Test Bank (1)

  • 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
    • 2: Exercises (35)
    • 2: Case Problems
    • 2: Test Bank (1)

  • 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
    • 3: Exercises (19)
    • 3: Case Problems
    • 3: Test Bank (1)

  • Chapter 4: Linear Programming Applications in Marketing, Finance, and Operations Management
    • 4.1: Marketing Applications
    • 4.2: Financial Applications
    • 4.3: Operations Management Applications
    • 4: Exercises (13)
    • 4: Case Problems
    • 4: Test Bank (2)

  • 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
    • 5: Exercises (9)
    • 5: Test Bank (1)

  • 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
    • 6: Exercises (20)
    • 6: Case Problems
    • 6: Test Bank (1)

  • 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
    • 7: Exercises (14)
    • 7: Case Problems
    • 7: Test Bank (2)

  • 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
    • 8: Exercises (22)
    • 8: Case Problems

  • 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
    • 9: Exercises (9)
    • 9: Case Problems
    • 9: Test Bank (1)

  • 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
    • 10: Exercises (18)
    • 10: Case Problems

  • 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: Other Waiting Line Models
    • 11.7: Single-Server Waiting Line Model with Poisson Arrivals and Arbitrary Service Times
    • 11.8: Multiple-Server Model with Poisson Arrivals, Arbitrary Service Times, and No Waiting Line
    • 11.9: Waiting Line Models with Finite Calling Populations
    • 11: Exercises (23)
    • 11: Case Problems

  • 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
    • 12: Exercises (8)
    • 12: Case Problems

  • 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
    • 13: Exercises (28)
    • 13: Case Problems

  • 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
    • 14: Exercises (17)
    • 14: Case Problems

  • 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
    • 15: Exercises (35)
    • 15: Case Problems (2)

  • Chapter 16: Markov Processes
    • 16.1: Market Share Analysis
    • 16.2: Accounts Receivable Analysis
    • 16: Exercises (8)
    • 16: Case Problems

  • Chapter 17: Linear Programming: Simplex Method
    • 17.1: An Algebraic Overview of the Simplex Method
    • 17.2: Tableau Form
    • 17.3: Setting up the Initial Simplex Tableau
    • 17.4: Improving the Solution
    • 17.5: Calculating the Next Tableau
    • 17.6: Tableau Form: The General Case
    • 17.7: Solving a Minimization Problem
    • 17.8: Special Cases
    • 17: Exercises (18)

  • Chapter 18: Simplex-Based Sensitivity Analysis with Duality
    • 18.1: Sensitivity Analysis with the Simplex Tableau
    • 18.2: Duality
    • 18: Exercises (14)

  • Chapter 19: Solution Procedures for Transportation and Assignment Problems
    • 19.1: Transportation Simplex Method: A Special-Purpose Solution Procedure
    • 19.2: Assignment Problem: A Special-Purpose Solution Procedure
    • 19: Exercises (5)

  • Chapter 20: Minimal Spanning Tree
    • 20.1: A Minimal Spanning Tree Algorithm
    • 20: Exercises (2)
    • 20: Case Problems

  • Chapter 21: Dynamic Programming
    • 21.1: A Shortest-Route Problem
    • 21.2: Dynamic Programming Notation
    • 21.3: The Knapsack Problem
    • 21.4: A Production and Inventory Control Problem
    • 21: Exercises (6)
    • 21: Case Problems


Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's An Introduction to Management Science: Quantitiatve Appropes to Decision Making, 15th edition, equips students with a sound conceptual understanding of the role that management science plays in the decision-making process. This edition reflects the latest developments in Microsoft® Office Excel® 2016. This market leader provides unwavering accuracy with emphasis on applications and timely examples. A hallmark problem-scenario approach introduces each quantitative technique within an applications setting. Students apply the management science model to generate solutions and recommendations for management. An all new WebAssign online course management system is available with this powerful management science solution.

Features:

  • Read It links under each question quickly jump to the corresponding section of the eBook.
  • Students can Talk to a Tutor for additional assistance through a link at the assignment level.
  • All questions contain detailed solutions to the problem, available to students at your discretion.
  • PowerPoint Presentations, Figures and Tables, Solutions Manuals, Case Solutions, Test Banks, and LINGO are available as textbook resources for instructors.
  • Downloadable DATAfiles (Excel and CSV), MODELfiles (Excel), Downloadable Online Chapters, Appendix A: Building Spreadsheet Models, Appendix B: Areas for the Standard Normal Distribution, Appendix C: Values of e, Appendix E: Self-Test Solutions, and Even-Numbered Answers are available as textbook resources for students and instructors.

Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

Question Group Key
E - End of Section Exercise
MI - Master It
MI.SA - Stand Alone Master It
CP - Case Problem
TB - Test Bank


Question Availability Color Key
BLACK questions are available now
GRAY questions are under development


Group Quantity Questions
Chapter 1: Introduction
1.E 13 001 003 004 005 007 008 009 011 012 013 015 017 019
1.TB 1 010
Chapter 2: An Introduction to Linear Programming
2.E 35 001 002 003 005 006 007 009 010 011 013 015 017 019 021 023 024 025 027 029 031 033 034 035 037 039 041 042 043 045 047 049 051 053 055 057
2.TB 1 010
Chapter 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution
3.E 19 001 002 003 005 006 007 009 011 012 013 015 017 019 021 023 025 027 029 031
3.TB 1 016
Chapter 4: Linear Programming Applications in Marketing, Finance, and Operations Management
4.E 13 001 003 005 007 009 011 013 015 017 019 021 023 025
4.TB 2 023 029
Chapter 5: Advanced Linear Programming Applications
5.E 9 001 003 007 009 010 011 013 015 017
5.TB 1 022
Chapter 6: Distribution and Network Models
6.E 20 001 002 003 005 006 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035
6.TB 1 019
Chapter 7: Integer Linear Programming
7.E 14 001 002 003 005 007 009 011 013 015 017 019 021 023 025
7.TB 2 008 031
Chapter 8: Nonlinear Optimization Models
8.E 22 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022
Chapter 9: Project Scheduling: PERT/CPM
9.E 9 004 008 010 014 016 018 020 022 024
9.TB 1 027
Chapter 10: Inventory Models
10.E 18 001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035
Chapter 11: Waiting Line Models
11.E 23 001 003 004 005 007 009 011 013 015 017 018 019 021 023 024 025 027 029 030 031 033 034 035
Chapter 12: Simulation
12.E 8 001 003 005 007 009 011 013 015
Chapter 13: Decision Analysis
13.E 28 001.MI 001.MI.SA 003 004 005 006.MI 006.MI.SA 007 008 009 011 013 014 015 016 017 018 019 020 021 022 023.MI 023.MI.SA 024 025 027 029 031
Chapter 14: Multicriteria Decisions
14.E 17 001 002 003 005 007 009 011 013 015 016 017 019 020 021 023 024 025
Chapter 15: Time Series Analysis and Forecasting
15.CP 2 002 002.alt
15.E 35 001 002 003 004.MI 004.MI.SA 005 006 007 007.alt 008 008.alt 009 009.alt 010 011.MI 011.MI.SA 012 013 014 015 017 018 019 021 021.alt 023 023.alt 024 025 026 026.alt 027 027.alt 028 028.alt
Chapter 16: Markov Processes
16.E 8 001 003 005 007 009 011 013 015
Chapter 17: Linear Programming: Simplex Method
17.E 18 001 003 005 007 009 011 013 014 015 017 019 021 023 024 025 026 027 029
Chapter 18: Simplex-Based Sensitivity Analysis with Duality
18.E 14 001 003 005 006 007 008 009 010 013 015 017 020 021 023
Chapter 19: Solution Procedures for Transportation and Assignment Problems
19.E 5 001 003 004 009 011
Chapter 20: Minimal Spanning Tree
20.E 2 001 003
Chapter 21: Dynamic Programming
21.E 6 001 003 004 005 007 009
Total 348