031025A Introduction to Optimization (5 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Description
Optimality criteria for unconstrained problems, convexity, gradient descent methods, Newton's and quasi Newton's method, least squares problems, KKT-conditions for constrained optimization, second order conditions in constrained optimization, simplex method for linear programming problems, duality in optimization.
Learning outcomes
After completing the course
- student can classify optimization problems and knows basic optimization algorithms for solving them.
- student is can formulate the necessary and sufficient conditions for optimality.
Additional information
Timing
Period 2
Target group
The target group includes, but is not restricted to, students who need to know practical optimization techniques in applied mathematics, such as the students in Wireless Communication Engineering and Computer Science Engineering.
Description of prerequisites
Prerequisites
Calculus I, Calculus II and Matrix Algebra. Numerical linear algebra course is highly recommended.