Skip to main content
MyCourses MyCourses
  • Schools
    School of Arts, Design, and Architecture (ARTS) School of Business (BIZ) School of Chemical Engineering (CHEM) –sGuides for students (CHEM) – Instructions for report writing (CHEM) School of Electrical Engineering (ELEC) School of Engineering (ENG) School of Science (SCI) Language Centre Open University Library Aalto university pedagogical training program UNI (exams) Sandbox
  • Service Links
    MyCourses - Instructions for Teachers - Teacher book your online session with a specialist - Digital tools for teaching - Personal data protection instructions for teachers - Instructions for Students - Workspace for thesis supervision Sisu Student guide Courses.aalto.fi Library Services - Resourcesguides - Imagoa / Open science and images IT Services Campus maps - Search spaces and see opening hours Restaurants in Otaniemi ASU Aalto Student Union Aalto Marketplace
  • ALLWELL?
    Study Skills Support for Studying Starting Point of Wellbeing About AllWell? study well-being questionnaire
  •   ‎(en)‎
      ‎(en)‎   ‎(fi)‎   ‎(sv)‎
  • Toggle Search menu
  • Hi guest! (Log in)

close

Can not find the course?
try also:

  • Sisu
  • Courses.aalto.fi

MS-E2122 - Nonlinear Optimization D, Lecture, 8.9.2022-1.12.2022

This course space end date is set to 01.12.2022 Search Courses: MS-E2122

  1. Home
  2. Courses
  3. School of Science
  4. department of...
  5. ms-e2122 - no...
 
Syllabus

MS-E2122 Nonlinear Optimization -- Fall 2022

  • MS-E2122 Nonlinear Optimization -- Fall 2022

    MS-E2122 Nonlinear Optimization -- Fall 2022

    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 (Nonlinear optimisation, in its most general form) 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 behind the main numerical algorithms available and how they can be applied to solve optimisation problems. At the end of the 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.  


    Practical matters

    Lecturer: Nuutti Hyvönen
    Assistants: Anton Saukkonen 

    • Teaching: lectures (24h) and exercise sessions (24h)
    • Assessment methods: Project assignments and homework assignments. 
    • Grading scale: 0-5
    • Study material: Lecture notes, lecture slides and exercises. Book (Nonlinear Programming, Theory and Algorithms by Bazaraa, Sherali and Shetty).
    • Language of instruction: English
    • Programming language: Julia http://www.julialang.org. Detailed information here.
    • Recommended platform: Aalto CS Jyputer Notebooks https://jupyter.cs.aalto.fi. Detailed information here.

    • icon for activity ForumAnnouncements Forum
    • icon for activity FileMS-E2122 Course syllabus -- Fall 2022 File PDF document

      Please read the course syllabus carefully for information on assessment, course content and administrative info.

    • Restricted Not available unless: Your User account contains (use: aalto.fi) contains aalto.fi
      icon for activity FilePoint totals and final grades File
      PDF document

Course home

Course home

Next section

Intro to Julia►
Skip Upcoming events
Upcoming events
Loading There are no upcoming events
Go to calendar...
  • MS-E2122 - Nonlinear Optimization D, Lecture, 8.9.2022-1.12.2022
  • Sections
  • MS-E2122 Nonlinear Optimization -- Fall 2022
  • Intro to Julia
  • Home
  • Calendar
  • Learner Metrics

Aalto logo

Tuki / Support
  • MyCourses help
  • mycourses(at)aalto.fi
Palvelusta
  • MyCourses rekisteriseloste
  • Tietosuojailmoitus
  • Palvelukuvaus
  • Saavutettavuusseloste
About service
  • MyCourses protection of privacy
  • Privacy notice
  • Service description
  • Accessibility summary
Service
  • MyCourses registerbeskrivining
  • Dataskyddsmeddelande
  • Beskrivining av tjänsten
  • Sammanfattning av tillgängligheten

Hi guest! (Log in)
  • Schools
    • School of Arts, Design, and Architecture (ARTS)
    • School of Business (BIZ)
    • School of Chemical Engineering (CHEM)
    • –sGuides for students (CHEM)
    • – Instructions for report writing (CHEM)
    • School of Electrical Engineering (ELEC)
    • School of Engineering (ENG)
    • School of Science (SCI)
    • Language Centre
    • Open University
    • Library
    • Aalto university pedagogical training program
    • UNI (exams)
    • Sandbox
  • Service Links
    • MyCourses
    • - Instructions for Teachers
    • - Teacher book your online session with a specialist
    • - Digital tools for teaching
    • - Personal data protection instructions for teachers
    • - Instructions for Students
    • - Workspace for thesis supervision
    • Sisu
    • Student guide
    • Courses.aalto.fi
    • Library Services
    • - Resourcesguides
    • - Imagoa / Open science and images
    • IT Services
    • Campus maps
    • - Search spaces and see opening hours
    • Restaurants in Otaniemi
    • ASU Aalto Student Union
    • Aalto Marketplace
  • ALLWELL?
    • Study Skills
    • Support for Studying
    • Starting Point of Wellbeing
    • About AllWell? study well-being questionnaire
  •   ‎(en)‎
    •   ‎(en)‎
    •   ‎(fi)‎
    •   ‎(sv)‎