Bachelor
2024/2025
Optimization Theory
Type:
Elective course (International Programme in Economics and Finance)
Area of studies:
Economics
Delivered by:
International College of Economics and Finance
When:
3 year, 3, 4 module
Mode of studies:
offline
Online hours:
16
Open to:
students of one campus
Language:
English
ECTS credits:
4
Contact hours:
56
Course Syllabus
Abstract
This course covers two main classes of optimization theory: statistic optimization and dynamic optimization. The part of static optimization covers such topics as unconstraint optimization and constraint optimization. The part of dynamic optimization covers such topics as calculus of variation, optimal control and dynamic programming. Despite the name of the course, it contains the practical part with applications in R language.
Expected Learning Outcomes
- a student can solve an unconstrained optimization problem
- a student can solve a constrained optimization problem
- a student can solve a calculus of variation problem
- a student can solve an optimal control problem
- a student can solve a dynamic programming problem
Course Contents
- unconstrained optimization
- constrained optimization
- calculus of variation
- optimal control
- dynamic programming
Assessment Elements
- home assignment 1
- quiz 1
- home assignment 2
- quiz 2
- final examIn order to get a passing grade for the course, the student must sit (all parts) of the final examination
- midterm
Interim Assessment
- 2024/2025 4th module0.4 * final exam + 0.1 * home assignment 1 + 0.1 * home assignment 2 + 0.2 * midterm + 0.1 * quiz 1 + 0.1 * quiz 2
Bibliography
Recommended Core Bibliography
- A first course in optimization theory, Sundaram, R. K., 2011
- Elements of dynamic optimization, Chiang, A. C., 1992
Recommended Additional Bibliography
- Токарев, В. В. Методы оптимизации : учебное пособие для вузов / В. В. Токарев. — Москва : Издательство Юрайт, 2024. — 440 с. — (Высшее образование). — ISBN 978-5-534-04712-7. — Текст : электронный // Образовательная платформа Юрайт [сайт]. — URL: https://urait.ru/bcode/539567 (дата обращения: 27.08.2024).