Optimization and Decision Support Methodologies

Before attending this course, students must have passed the Operations Research course unit (2nd year of this degree).

A learning strategy based on the experimentation of the material exposed in the theoretical class is used, either through the resolution of theoretical-practical exercises on the topics covered, or through the computational resolution of the same.

• In the theoretical component the subject is exposed, while the active participation of students is encouraged by frequently asking questions to be answered by them.
• In the theoretical-practical component, students manually solve exercises for the application of the theoretical component.
• In the practical-laboratory component, students solve computationally various types of problems, using Python libraries.

Based on the concepts acquired in Operations Research, in this course it is intended that students broaden their knowledge in the areas of optimization and decision support. In this sense, methodologies will be introduced to be applied to decision problems that are more complex than those previously studied, such as problems involving multiple objectives, integer variables, among others. After attending this course, students should: 1 – Know and understand the fundamental characteristics of the most representative problems of optimization and decision support; 2 – Identify the different approaches that can be used to solve them; 3 – Solve simple practical problems using the appropriate optimization and decision support algorithms and interpret the obtained solution(s); 4 – Be able to computationally implement some of the algorithms / use computational tools, to solve the types of problems addressed.

Theoretical program

     0. Linear Programming – review of basic concepts
     1. Post-Optimization and Sensitivity Analysis
     2. Integer Linear Programming
     3. Multi-Objective Linear Programming
     4. Goal Programming

Theoretical-practical/practical program:

• Manual / computational resolution of several types of problems 

NAO

Recommended:

• Documentation that supports classes (available on Moodle)
• Hillier, F. S.; Lieberman, G. J. (1995) – Introduction to Operations Research (6th ed.). New York: McGraw-Hill (available at ISEC’s Library: 3-9-31 (ISEC) – 08145; The 10th edition (2015) of this book is available for download in: https://pt1lib.org/book/3426899/3de006)

Additional:

• Ravindran, A.; Phillips, D. T.; Solberg, J. J. (1987) – Operations Research: Principles and Practice. (2nd ed.). New York: John Wiley (available at ISEC’s Library: 3-9-57 (ISEC) – 09253)
• Taha, H. A. (1995) – Operations research: an introduction (5th ed.). London: Prentice-Hall (available at ISEC’s Library: 3-9-29 (ISEC) – 07857)
• Murthy, P. R. (2007) – Operations Research (2nd ed.). New Delhi: New Age International Publishers (PDF available for download in: https://easyengineering.net/operations-research-p-ramamurthy/)