MS-C2105 - Introduction to Optimization, 01.03.2021-12.04.2021
This course space end date is set to 12.04.2021 Search Courses: MS-C2105
Topic outline
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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.- See Schedule 2021- 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
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Syllabus File PDF
- Teaching: Lectures (24h) and exercise sessions (24h)