| TNK047 |
Optimization and system analysis, 6 ECTS credits.
/Optimering och systemanalys/
For:
KTS
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Prel. scheduled
hours: 48
Rec. self-study hours: 112
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Area of Education: Science
Main field of studies: Mathematics, Applied Mathematics
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Advancement level
(G1, G2, A): G2
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Aim:
The course aims at further insight in modelling and optimization of decision problems. Models for decision analysis is analyzed, including models and methods for optimization problems with discrete variables and for problems from game theory. The students can, after the completion of the course, formulate basic models in decision analysis - solve and analyze the formulated models - apply the analysis to practical problems.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Linear algebra, Optimization,Statistics and probability.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Organisation:
Lectures, exercises and laboratory work.
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Course contents:
The contents of the course cover mathematical modelling and solution methods. Great weight is given to modelling of problems in decision analysis. Some weight is given to solution techniques for discrete optimization problems. The discussed model types include discrete optimization, and game models. Solution algorithms for these problem types are developed based on the methods and algorithms in the basic optimization course.
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Course literature:
Optimeringslära, Lundgren et al. (also used in TNK049) and parts of "Business Statistics: Contemporary Decision Making", K. Black." available on the Internet, alternatively part of Decision Analysis, Location Models, and Sceduling Problems, H.A. Eiselt och C.-L.Sandblom, Springer, ISBN 3-540-40338-8.
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Examination: |
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Written examination
Laboratory work
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3 ECTS
3 ECTS
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Course language is Swedish.
Department offering the course: ITN.
Director of Studies: Erik Bergfeldt
Examiner: Joakim Ekström
Link to the course homepage at the department
Course Syllabus in Swedish
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