Topic outline

  • Why this course?


    Mathematical optimisation is one of the cornerstones of fields such as Machine Learning, Artificial Intelligence, and Operations Research. Most decision support methods have, at some level, a mathematical optimisation method at its core, and it is precisely these methods that we will learn in this course.

    Mathematical optimisation is a powerful framework in which one seeks to find variable values within a domain that maximise (or minimise) the value of a given function. Using the analogy that variables represent decisions or parameters to be defined and the function is a measure of performance, one can use that framework to support decision making in a wide range of applications, from planning industrial chemical plants to training models that learn from data. 

    In this course, the student will learn the basic optimisation theory, how to formulate problems and how they can be solved. Linear, integer, and nonlinear optimisation will be covered in the course. At the end of this course, it is expected that the student will be capable of analysing the main characteristics of an optimisation problem and decide what is the most suitable method to be employed for its solution.  

    Start

    - Sign up to one exercise group in http://oodi.aalto.fi
    - The course starts with a (prerecorded) lecture on Wed 3rd of March. See Panopto.
    - Depending on your exercise group, the first exercise session will be on Thu-Fri 4th-5th Mar.
    - The first deadline (Quiz 1) will be on Sun 14th Mar. The only submissions on this course are the quizzes and the exam.
    - Log in to MyCourses with Aalto account to see all contents.

    Exercise groups  (in Zoom+Slack)

    Ex1
    Ex2
    Assistant email at aalto.fi Zoom ID
    H01  Mon 12
     Thu 8
     Jarkko
    jarkko.jalovaara
    629 5305 6778
    H02  Tue 10
     Thu 10
     Jaan de.tollander 656 3917 1761
    H03  Tue 10
     Thu 12
     Mikko mikko.a.kaivola 613 8921 8250
    H04  Wed 10
     Fri 8
     Paula paula.weller 688 3661 3997
    H05  Wed 12
     Fri 10
     Leevi leevi.korkeala 623 2953 0329
    H06
     Tue 12
     Thu 12
     Alpi alpi.jokinen 648 8247 7944
    H07  Tue 12
     Thu 10
     Elmer elmer.bergman
    634 6638 1745

    See also videos for the demo exercises. Disclaimer: These are experimental, and not necessarily available for all demo problems.

    Practical matters

    Lecturer: Fabricio Oliveira

    Head Assistant: Paula Weller

    • Teaching: Lectures (24h) and exercise sessions (24h)
    • Assessment method: Exam+five quizzes (100+10 pts).
    • Grading scale: 0-5. Total of 91+ points yields a 5.
    • Study material: Lecture slides and exercises. Books: (main Operations Research: An Introduction by Hamdy Taha, Pearsons 8th edition or above, and secondary Operations Research: Applications and Algorithms by Wayne L. Winston).
    • Language of instruction: English