Basics of Operations Research

Course: Informatics

Structural unit: Faculty of Computer Science and Cybernetics

Title
Basics of Operations Research
Code
ОК.28
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
4
Learning outcomes
PH04. Perform mathematical description, analysis and synthesis of discrete objects and systems, using the concepts and methods of discrete mathematics and algorithm theory. PH10. Have methods for choosing rational methods and algorithms for solving mathematical problems
Form of study
Full-time form
Prerequisites and co-requisites
to study the discipline "Operations Research" the student must meet the following requirements: Know: 1. Linear algebra: construction of a basis, solution of systems of linear algebraic equations; 2. classical methods of mathematical analysis, probability theory. Be able to: 1. to study the qualitative characteristics of the constructed mathematical models. 2. formulate mathematical optimization problems for such models. 3. apply classical methods for the study of applied problems of mathematical programming. Have skills: 1. of using classical methods of mathematical analysis and linear algebra. 2. of search and analysis of information in open sources.
Course content
The aim of the discipline is to study the basics of operations research and mathematical programming, their models and methods that are most often used to quantify management decisions and mathematical modeling of economic processes.
Recommended or required reading and other learning resources/tools
1. Popov YU.D., Tyuptya V.I., Shevchenko V.I. Metody optymizatsiyi — Kyyiv: Elektronne vy-dannya. Elektronna biblioteka fakulʹtetu kibernetyky Kyyivsʹkoho natsionalʹnoho uni-versytetu imeni Tarasa Shevchenka, 2003, — 215 s. 2. Zaychenko YU. P. Doslidzhennya operatsiy. Pidruchnyk / YU. P. Zaychenko. – 7-me vyd., pere-robl. ta dopov. – Kyyiv : Vydavnychyy dim «Slovo», 2006. – 816 s. 3. Khemdi. A. Takha. Vvedenye v yssledovanye operatsyy, 10-e yzdanye. — M.: Vylʹyams, 2016. 912 s. 4. Nefʹodov YU. M. Metody optymizatsiyi v prykladakh i zadachakh : navchalʹnyy posibnyk / YU. M. Nefʹodov, T. YU. Balytsʹka. – Kyyiv : Kondor, 2011. – 324 s. 5. Dzyuban I. YU. Metody doslidzhennya operatsiy / I. YU. Dzyuban, O. L. Zhyrov, O. H. Okhri-menko. – Kyyiv : IVTS «Vydavnytstvo «Politekhnika », 2005. – 108 s. 6. Nakonechnyy S. I. Matematychne prohramuvannya: navch. posib. / S. I. Nakonechnyy, S. S. Savina. – Kyyiv : KNEU, 2003. – 452 s.
Planned learning activities and teaching methods
Lectures, practice work, independent work, processing recommended literature, homework.
Assessment methods and criteria
Semester assessment: Maximum number of points that can be obtained by a student: 100 points: 1. Test work № 1: PH 1.1, PH 2.1, PH 2.2, PH 2.3 - 20/10 points. 2. Test work № 2: PH 1.1, PH 2.1, PH 2.2, PH 2.3 - 20/10 points 3. Test work № 3: PH 1.1, PH 2.1, PH 2.2, PH 2.3 - 20/10 points Final assessment (in the form of an exam): - Maximum number of points that can be obtained by a student: 40 points. - Learning outcomes to be evaluated: PH 1.1, PH 2.1, PH 2.2, PH 2.3, PH 2.4, PH 3.1, PH 3.2, PH 4.1, PH 4.2. - Form of conducting: written. - Types of tasks: 4 written tasks (2 theoretical questions and 2 practical tasks). - A student receives an overall positive grade in the discipline if his grade for the exam is not less than 24 (twenty four) points. - A student is admitted to the exam if during the semester he: o scored at least 36 points; performed and timely submitted at least 2 (two) independent works from the list of proposed works;
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Andrii V. Zavorotynskyi
Operations Research
Faculty of Computer Science and Cybernetics
Roman Ya. Yakymiv
Operations Research
Faculty of Computer Science and Cybernetics
Inna S. Rybalko
Operations Research
Faculty of Computer Science and Cybernetics
Ivan K. Matsak
Operations Research
Faculty of Computer Science and Cybernetics