Search course

Use the search function to find more information about the study programmes and courses available at Chalmers. When there is a course homepage, a house symbol is shown that leads to this page.

Graduate courses

Departments' graduate courses for PhD-students.

​​​​
​​

Syllabus for

Academic year
MVE165 - Applied optimisation
 
Syllabus adopted 2008-02-27 by Head of Programme (or corresponding)
Owner: MPENM
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: English

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0107 Examination 7,5c Grading: TH   7,5c   Contact examiner

In programs

MPALG COMPUTER SCIENCE - ALGORITHMS, LANGUAGES AND LOGIC, MSC PROGR, Year 2 (elective)
MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (elective)
MPSYS SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR - All specializations, Year 1 (elective)

Examiner:

Professor  Michael Patriksson



  Go to Course Homepage

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 in several variables.

Aim

A main purpose with the course is to give the students an overview of
important areas where optimization problems often are considered in
applications, and an overview of some important practical techniques for
their solution. Another purpose of the course is to provide insights into
such problem areas from both a application and theoretical perspective,
including the the analysis of an optimization model and suitable choices
of
solution approaches. Work with concrete problems during the course enable
the establishment of these insights.

lösningsansatser. Självständigt arbete med konkreta problem under
kursens stadfäster och bekräftar sedan dessa insikter.

Learning outcomes (after completion of the course the student should be able to)

After the completion of the course the student should understand the main
principles behind the modelling of optimization problems and have a clear
overview of the most important classes of such problems. Within each class
the student shall have reached insights about at least one basic solution
technique and be able to complete an entire optimization project in each
class, including all parts of the chain modelling --> model analysis -->
implementation in suitable algorithm/software --> (sensitivity) analysis
of an optimal solution.

Content

This course describes with the aid of practical cases how optimization problems are modelled and solved in practice. In addition to a lecture series given by staff at MV there is a series of guest lectures mainly by staff at other departments of Chalmers and Göteborg University. The contents of the course may therefore vary in terms of topics between the years, but a common thread is that the course is about the practical solution of optimization problems. Some of th guest lectures are connected to project assignments, which also is the main basis for the examination.

Some typical problems, algorithm techniques and software that will be covered and utilized often over the years are:

Investment
Blending
Production planning
Queueing theory
Routing and transport
Multi-objective optimization
Inventory planning

Dynamic programming
Markov chains
Heuristics
Simulation
Simplex and interior points methods for LP

AMPL
Cplex
Matlab

Organisation

Lecture series of mathematical material
Guest lecture series of practical material
Project work
Student presentations of projects

Literature

An Introduction to Optimization, by N. Andreasson, A. Evgrafov, and M. Patriksson, published by Studentlitteratur in 2005
Operations Research, 8th edition, by H. A. Taha 2007

Examination

Project assignments, oral and written presentations and opposition


Page manager Published: Thu 04 Feb 2021.