Operations Research

Course: Applied Programming

Structural unit: Faculty of information Technology

Title
Operations Research
Code
ОК 9
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
2 Semester
Number of ECTS credits allocated
4
Learning outcomes
As a result of studying the discipline, the student acquires the following competencies: Knowledge: basic terms, models and typical problems of operations research, formulation of problems of linear, integer, nonlinear and stochastic programming and methods of solving problems of this class. Ability to analytically solve linear, integer and nonlinear programming problems, solve optimization problems using MS Excel Solver and AMPL software. Communications: development of teamwork skills in students, ability to justify one's own view on the problem being solved, to report the results of one's own work.
Form of study
Full-time form
Prerequisites and co-requisites
- Successful mastering of the disciplines "Linear Algebra and Analytical Geometry", "Mathematical analysis", "Discrete mathematics", "Probability theory and mathematical statistics", "Fundamentals of algorithmization and programming". − Know the basics of linear algebra, differential and integral calculus, algorithmization and programming, basic laws of distribution of random variables. - Be able to perform operations on vectors and matrices, solve linear systems algebraic equations, find limits of functions, differentiate functions of one and of many variables, examine the function at the extremum, calculate numerical values characteristics of random variables, develop algorithms and program them.
Course content
The discipline "Operations Research" aims to study the conceptual foundations related to optimization methods used in various applied fields of human activity. Students will learn how to carry out a formalized description of operations research problems, master mathematical methods for solving optimization problems of linear, integer, nonlinear and stochastic programming, get acquainted with software tools for solving this class of problems. The purpose of the discipline is to get acquainted with the basic concepts, typical problems and optimization models and methods of solving optimization problems, the formation of knowledge and skills regarding the use of modern software tools to solve operations research problems.
Recommended or required reading and other learning resources/tools
1. Mathematical methods of operations research: a textbook / E. A. Lavrov, L. P. Perhun, V. V. Shendryk and others. Sumy: Sumy State University, 2017. 212 p. 2. Operations research. Synopsis of lectures / Compiler: O.I. Lysenko, I.V. Alekseeva, K: NTUU "KPI", 2016. 196 p. 3. Ivanyuta I.D., Rybalka V.I., Rudomino-Dusyatska I.A. Workshop on mathematical programming: teaching. manual Kyiv: Slovo Publishing House, 2008. 296 p. 4. Rzhevsky S. V., Aleksandrova V. M. Operations research: textbook. Kyiv: Akademvydav, 2006. 560 p. 5. NEOS Server. State-of-the-Art Solvers for Numerical Optimization. URL: https://neos-server.org/neos/ 6. AMPL. URL: https://ampl.com
Planned learning activities and teaching methods
Lectures, laboratory classes, individual work
Assessment methods and criteria
The level of achievement of the planned learning outcomes is defined as the total grade for the student's work in the semester and the result of the final control in the form of a written exam. The condition for receiving a positive final grade for a discipline is to achieve at least 60% of the maximum possible number of points - 60 points out of 100. The student is allowed to take the exam on the condition that he completes the 8 laboratory works and the test provided by the plan, which in the end must be at least the recommended minimum of 36 points (60% of the maximum possible number of points that the student can receive for work in the semester). The exam is conducted in the form of a test with 20 questions, among which 40% are theoretical and 60% are practical. To receive a positive grade, a student must receive at least 24 points (60% of the maximum possible number of points) on the exam.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

DEPARTMENT OF APPLIED INFORMATION SYSTEMS
Faculty of information Technology

Departments

The following departments are involved in teaching the above discipline

DEPARTMENT OF APPLIED INFORMATION SYSTEMS
Faculty of information Technology