COURSE SYLLABUS

Numerics for Optimization and PDE 7.5 Credits

Numerik för optimering och PDE
Second cycle, C7005M
Version
Course syllabus valid: Autumn 2018 Sp 1 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.

Syllabus established
by Mats Näsström 13 Feb 2017

Last revised
by Mats Näsström 15 Feb 2018

Education level
Second cycle
Grade scale
G U 3 4 5
Subject
Scientific Computing
Subject group (SCB)
Mathematics

Entry requirements

Mathematics including linear algebra and multivariable calculus (e.g. M0029M-M0032M at LTU). Programming skills in Matlab or in some other programming language. Knowledge of basic Numerics ( e.g., C0004M or S7013E at LTU)


More information about English language requirements


Selection

The selection is based on 20-285 credits



Course Aim

After the  course the student should:

1. Knowledge and understanding

  • Be able to explain  how different  sources of errors affect the accuracy in computations.
  • Be able to explain  basic techniques, such as linearization and discretization, for numeric computing.

2. Skills and abilities

  • Be able to use numerical methods for solving advanced computational problems, such as  e.g. optimization problems and  partial differential equations.
  • Be able to implement different methods on a computer and to use existing software, e.g., matlab.

3. Assessment  and attitudes

  • Be able to judge different methods regarding strengths, weaknesses and usability.
  • Be able to judge the reliability of computed results.
  • Be oriented about current research in the areas.

Contents

Numerical  methods for  linear and nonlinear optimization  and for  ordinary and partial differential equations.


Realization

Lectures  and supervision in connection to assignments.

Most part of the studies are performed, outside the scheduled lectures, by working with different assignments were different algorithms are implemented and analysed.

The students will here be trained in understanding and implementing different algorithms and to judge them. The students are also trained in structuring problems and to communicate  computational  issues and how to solve them.


Examination

Assignments  and  an exam  that can be written or oral.


Remarks
C7005M have several components corresponding with the course C7004M thus cannot be included in the degree together with C7004M.

Examiner
Inge Söderkvist

Literature. Valid from Autumn 2017 Sp 1 (May change until 10 weeks before course start)
• Nocedal J, Wright S. J., Numerical Optimisation, Second ed, Springer 2006,
• Notes

Course offered by
Department of Engineering Sciences and Mathematics

Items/credits
NumberTypeCreditsGrade
0001Exam4.0TG G U 3 4 5
0002Assignments3.5TG U G#

Study guidance
Study guidance for the course is to be found in our learning platform Canvas before the course starts. Students applying for single subject courses get more information in the Welcome letter. You will find the learning platform via My LTU.