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Class Quantitative Optimization Methods

  • Presentation

    Presentation

    Provides knowledge, skills and mathematical tools in the field of operations research, which are essential for management and engineering.

  • Code

    Code

    ULHT41-22919
  • Syllabus

    Syllabus

    1. General introduction to Operations Research.
    2. Structuring and modeling real-world problems.
    3. Predictive and explanatory models.
    4. Exact and approximate optimization models.
    5. Linear programming (LP).
      1. LP modeling.
      2. Solving LP models through the graphical method.
      3. Solving LP models through the simplex method.
    6. Mixed integer linear programming.
    7. Non-linear programming.
    8. Heuristics.
    9. Multicriteria analysis.
  • Objectives

    Objectives

    The main objective of this course (Quantitative Methods of Optimization) is to prepare students to address and solve complex real-world optimization problems, namely in the fields of management and engineering. Therefore, it is intended to:

    • Ensure basic knowledge of Operations Research.
    • Teach how to mathematically formulate optimization problems.
    • Teach solution methods for optimization problems.
    • Address specific problems relevant to management and engineering.
    • Clarify the differences between the different types of optimization models and their solution methods.
    • Provide basic knowledge to use MS Excel to solve optimization problems.
  • References

    References

    • Hillier, F.S., Lieberman, G.J. - Introduction to Operations Research. 11th Ed. McGraw-Hill, 2021. ISBN: 9781259872990.
    • Hillier, F.S., Lieberman, G.J. - Introdução à Pesquisa Operacional. 9ª Ed. McGraw-Hill, 2013. ISBN: 9788580551181.
    • Williams, H. P. - Model building in mathematical programming. 5th Ed. John Wiley & Sons, 2013. ISBN: 9781118443330.
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