Third-Cycle Courses

Faculty of Engineering | Lund University

Details for Course FMA275F Numerical Optimization

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  • FMA275F
  • Temporary
Course Name
  • Numerical Optimization
Course Extent
  • 7.5
Type of Instruction
  • Third-cycle course
Administrative Information
  • 7151 (Centre of Mathematical Sciences / Mathematics)
  •  -02-17
  • FN1/AndersGustafsson

Current Established Course Syllabus

  • English
  • If sufficient demand
  • The aim of the course is to give good knowledge about modern numerical optimization algorithms especially about those suitable for large-scale problems - in particular their practical strengths and weaknesses and a deeper understanding of the basic principles behind them - in order to be able to use them in research.
  • Line search and trust-region methods, conjugate gradient and quasi-Newton methods, large-scale optimization, derivative-free methods, least-squares, nonlinear equations, theory and fundamentals of algorithms for nonlinear optimization with constraints, interior-point methods, quadratic and sequential quadratic programming, penalty and augmented Lagrangian methods.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • be able to describe the main features of modern optimization algorithms which are used in practice.
    be able to explain the basic principles for the algorithms that are covered by the course.
    be able to describe the differences between algorithms with respect to properties and behaviour.
Competences and Skills
  • For a passing grade the doctoral student must
  • be able to independently identify and formalize problems relevant for industry or research as optimization problems.
    show good ability to analyse an optimization problem and suggest a suitable numerical algorithm as well as to implement it in MATLAB.
    be able to give a qualitative comparison of the strengths and weaknesses of different numerical algorithms within the course (with respect to convergence, speed, stability, large-scale properties etc).
    be able to present a solution to mathematical problems within the course scope that is terminologically adequate, well structured and logically correct.
Judgement and Approach
  • For a passing grade the doctoral student must
Types of Instruction
  • Seminars
  • Seminars by the course participants
Examination Formats
  • Written assignments
  • Seminars given by participants
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
Selection Criteria
  • Nocedal, J. & Wright, S.: Numerical Optimization. Springer, 2006. ISBN 9780387303031.
Further Information
  • It should be at least seven potential participants for the course to be given.
Course code
  • FMA275F
Administrative Information
  •  -02-17
  • FN1/AndersGustafsson

All Established Course Syllabi

1 course syllabus.

Valid from First hand in Second hand in Established
Autumn 2015 2016‑01‑11 13:38:21 2016‑02‑02 15:35:06 2016‑02‑17

Current or Upcoming Published Course Occasion

No matching course occasion was found.

All Published Course Occasions

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0 course occasions.

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