Semester of Instruction
Objectives and Content
The course contains solution methods for linear optimization models. Topics that are covered include the simplex method and the interior point methods for linear programming, network algorithms, duality theory and sensitivity analysis.
Upon completion of INF270 Introduction to Solution Methods in Optimization, the student is supposed to be able to
- formulate a combinatorial optimization problem efficiently
- explain the mathematical theory underlying the solution methods.
- analyze the solution to a linear optimization problem
Required Previous Knowledge
At least 60 ECTS in computer science, preferably including some mathematics
Recommended mathematics: Calculus I and II and linear algebra.
Recommended Previous Knowledge
INF101 (Program Development Methodologies), MNF 130 (Discrete Structures), MAT 121 (Linear Algebra) and MAT 160 (Scientific computing I).
Compulsory Assignments and Attendance
Compulsory assignments are valid two semesters, the semester of the approval and the following semester.
Forms of Assessment
Written exam. It is opportunity for grades on exercises, which can be included in the final grade. If less than 20 students are taking the course, it can be oral exam.
Aids allowed will be announced on My Space in the beginning of each semester.
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
I 172: 10 ECTS