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English

Published by Pearson (November 21, 2023) © 2023

Bernard Taylor
    Pearson eTextbook ( 1 year access )
    €41,99

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    ISBN-13: 9781292439952

    Introduction to Management Science, Global Edition ,13th edition

    Language: English

    Product Information

    For undergraduate courses in management science. 

    A logical, step-by-step approach to complex problem-solving

    Introduction to Management Science gives readers a strong foundation in how to make decisions and solve complex problems using both quantitative methods and software tools. In addition to extensive examples, problem sets, and cases, the 13th Edition incorporates Excel 2016 and other software resources, developing readers’ ability to leverage the technology they will use throughout their careers. By practicing these modeling techniques, readers gain a useful framework for problem-solving that they can then apply in the workplace.

    1. Management Science
    2. Linear Programming: Model Formulation and Graphical Solution
    3. Linear Programming: Computer Solution and Sensitivity Analysis
    4. Linear Programming: Modeling Examples
    5. Integer Programming
    6. Transportation, Transshipment, and Assignment Problems
    7. Network Flow Models
    8. Project Management
    9. Multicriteria Decision Making
    10. Nonlinear Programming
    11. Probability and Statistics
    12. Decision Analysis
    13. Queuing Analysis
    14. Simulation
    15. Forecasting
    16. Inventory Management
    • Appendix A: Normal and Chi-Square Tables
    • Appendix B: Setting Up and Editing a Spreadsheet
    • Appendix C: The Poisson and Exponential Distributions

    Solutions to Selected Odd-Numbered Problems

    The following items can be found on the companion website that accompanies this text:

    • Module A: The Simplex Solution Method
    • Module B: Transportation and Assignment Solution Methods
    • Module C: Integer Programming: The Branch and Bound Method
    • Module D: Nonlinear Programming Solution Techniques
    • Module E: Game Theory
    • Module F: Markov Analysis
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