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Syllabus for

Academic year
TMA947 - Optimization, first course
 
Owner: TM
5,0 Credits (ECTS 7,5)
Grading: TH - Five, Four, Three, Not passed
Level: C
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: English

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0103 Laboratory 1,0 c Grading: UG   1,0 c    
0203 Examination 4,0 c Grading: TH   4,0 c   12 Mar 2007 am V,  30 Aug 2007 am V

In programs

TM Teknisk matematik, Year 1 (compulsory)
EMMAS MSc PROGR IN ENGINEERING MATHEMATICS, Year 1 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING - Algorithms, Year 4 (compulsory)

Examiner:

Professor  Michael Patriksson


Replaces

TMA946   Applied optimization


Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

Linear algebra, analysis in one and several variables

Aim

The course is an introductory course in optimiza-tion. It serves to provide (1) basic knowledge of important classes of optimization problems and application areas of optimization models and methodologies; (2) practice in describing relevant parts of a real-world problem in a mathematical optimization model; (3) knowledge of and insights into the basic mathematical theory which underlies the principles of optimality; (4) examples of optimization methods that have been and can be developed from this theory in order to solve practical optimization problems.

Content

The course is broad in its contents, but has its main focus on
optimization problems in continuous variables, and can within this framework
be separated into two main areas:

Linear programming: Linear optimization models, linear programming
theory and geometry, the Simplex method, duality, interior point methods,
sensitivity analysis, modelling languages;

Nonlinear programming: Nonlinear optimization models, convexity theory,
optimality conditions, Lagrangian duality, iterative algorithms for
optimization problems with or without constraints, relaxations, penalty
functions.

We may also touch upon three other important problem areas within
optimization: integer programming, network optimization, and optimization
under uncertainty.

Organisation

Lectures, exercises, computer exercises, and a project
assignment.

Literature

Lecture notes.
Additional literature: Linear and Nonlinear Programming
(S G Nash and A Sofer, 1996)

Examination

Passed project assignment gives one credit.

Passed written exam gives the remaining four credits.


Page manager Published: Thu 03 Nov 2022.