Valid from: Spring 2021
Decided by: Professor Thomas Johansson
Date of establishment: 2021-03-01
Division: Mathematics
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course codes: FMAF35, FMA240
Teaching language: English
In science, technology and economics, linear and combinatorial optimization problems appear more and more often. The most well known example is linear programming, where the so called simplex method has been of utmost importance in industry since it was invented in the middle of the 20th century. Other important problems, e.g. for effective data processing, contain discrete variables, for example integers. In connection with these, the importance of combinatorial methods has grown. The aim of the course is to make the students aware of problems in linear and combinatorial optimization which are important in the applications, and to give them knowledge about mathematical methods for their solution. The aim is also to make the students develop their ability to solve problems, with and without the use of a computer.
Knowledge and Understanding
For a passing grade the doctoral student must
Competences and Skills
For a passing grade the doctoral student must
Linear programming. Integer programming. Transport problems. Assignment problems. Maximal flow. Local search. Simulated annealing. Genetic optimization. Neural networks. Dynamic programming. Algorithm complexity.
Types of instruction: Lectures, laboratory exercises, exercises
Examination formats: Written exam, oral exam, miscellaneous.
Computer sessions. Written and/or oral test, to be decided by the examiner. Some minor projects should be completed before the exam.
Grading scale: Failed, pass
Examiner:
Assumed prior knowledge: FMAB20 Linear Algebra.
Course coordinators:
Web page: http://www.ctr.maths.lu.se/course/linkomboptnykod/