Mathematical Optimization

Course: Economics (English/Ukrainian Taught)

Structural unit: Faculty of Economics

Title
Mathematical Optimization
Code
ОК 14
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2018/2019
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
11
Learning outcomes
Know: - methods of linear optimization - methods of unconstrained optimization To be able - to construct standard maximum/minimum linear programming problems starting from words to constraints and objective function - to solve the economic and mathematical linear optimization models - to apply knowledge to solve practical optimization problems
Form of study
Full-time form
Prerequisites and co-requisites
1. Know the basic concepts of mathematics and probability theory and mathematical statistics; he basic concepts and theorems of linear programming 2. Possess the basic methods for solving systems of linear equations and inequalities; posssess the skills to build optimization models and basic methods for solving linear and unconstrained optimization problems.
Course content
The course structure has two modules: Content module 1. Linear optimization Content module 2. Unconstrained Optimization Module 1. “Linear Optimization” is devoted to the study of linear optimization techniques, for example graph, table and simplex methods, sensitivity analysis, and applications of linear optimization. Module 2. “Unconstrained Optimization” covers unconstrained optimization methods (convergent algorithms, conjugate gradient methods, and etc.). Content module 3. Nonlinear Optimization Content module 4. Dynamic Optimization
Recommended or required reading and other learning resources/tools
1. Raju N.V.S. Operations Research: Theory and Practice, BSP Publications, 2020. 2. Raymond A. Barnett, Michael R. Ziegler, and Karl E. Byleen, Finite Mathematics for Business, Economics, Life Sciences, And Social Sciences. Thirteenth edition. Global edition. Pearson, 2015. 3. Andr´easson Niclas, Evgrafov Anton, and Patriksson Michael, An Introduction to Optimization: Foundations and Fundamental Algorithms, 2005. 4. Wickens M. Macroeconomic Theory: A Dynamic General Equilibrium Approach - Second Edition. Princeton University Press; 2nd edition, 2012. 5. Hoy M., Livernois J., McKenna C., Rees R. and Stengos T., Mathematics for Economics, vol. 1, 3 ed., The MIT Press, 2011. 6. Intriligator, M.D., Mathematical Optimization and Economic Theory, SIAM, 2002.
Planned learning activities and teaching methods
Lecture, practice, individual student’s self-study, final test, exam
Assessment methods and criteria
The forms of evaluation (max. 100 points, min – 60 points): - semester evaluation: 1. Test (RS 1.1-1.2; 2.1-2.3) - 10 points /6 points; 2. Oral examination (RS 1.1-1.2; 2.1-2.3) - - 5 points / 2 points; 3. Solving problems (RS 1.1-1.2; 2.1-2.3) - 5 points / 2 points; 4. Module test (2 MT, 15 points max. each) (RS 1.1-1.2; 2.1-2.3) - 30 points / 20 points; 5. Individual students’ self-study (1 project, 25 points) (RS 1.1-1.2; 2.1-2.3) - 25 points / 15 points; 6. Final test (RS 1.1-1.2; 2.1-2.3) - 25 points / 15 points.
Language of instruction
English

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline