The aim of this advanced course is to give the students insights onto basic optimization theory and ability to master efficient algorithms and numerical methods for solving all major classes of optimization problems. The course contains the following themes. Linear programming (LP): brief summary of the theory and algorithms LP models such as asset/liability cash flow matching, short term financing; capital budgeting problem, Solution of nonlinear equations, Model computation of internal rate of return. Nonlinear programming: theory and algorithms for unconstrained and constrained optimization, quadratic models, portfolio optimization. Statistical models: Maximum likelihood estimation. Linear and nonlinear parameter estimation: theory and algorithms, models, power system analysis, volatility estimation. Practical solutions of optimization problems in Matlab using the Optimization Toolbox and self-implemented methods. Examples of applications: defining setting up, solving and analyzing results from optimization models from mathematical finance, statistics, power system analysis and problems related to environmental issues.
Occasions for this course
Autumn semester 2021
2021-11-08 - 2022-01-16 (part time 50%)
Course syllabus & literatureSee course plan and literature list (MAA700)
At least 120 credits totally from these areas: technical, natural sciences, business administration or economics where Operations Research 7,5 credits is included as well as some course or courses the learning outcomes of which include knowledge of some programming language or of use of MATLAB.
In addition Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.