Research of Operations

Course: Applied Mathematics

Structural unit: Faculty of Computer Science and Cybernetics

Title
Research of Operations
Code
ННД.26
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
4 Semester
Number of ECTS credits allocated
3
Learning outcomes
PH02. Have basic principles and methods of mathematical, complex and functional analysis, linear algebra and number theory, analytical geometry, theory of differential equations, including partial differential equations, probability theory, mathematical statistics and random processes, numerical methods. PH14. Demonstrate the ability to self-study and continue professional development.
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. Theory of linear algebra, construction of the 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. Possess: 1. skills of using classical methods of mathematical analysis and theory of linear algebra. 2. skills of formulation and algorithms for solving linear programming problems. 3. skills of search and analysis of information in open sources.
Course content
Block 4. Discrete and integer programming. Topic 7. Discrete programming (DP). The problem of optimal assignments. Topic 8. Methods of segments of solving problems of integer linear programming Topic 9. The method of branches and borders Block 5. Elements of game theory. Topic 10. INTRODUCTION to game theory. Matrix games. Topic 11. Mixed strategies and the relationship with PLL Test work Block 6. Nonlinear programming (NP). Topic 12. Review of methods and models of emergency. General issues of nonlinear programming. Topic 13. Convex programming (OP). Topic 14. Gradient methods and the method of possible directions Topic 15. Methods of penalty and barrier functions
Recommended or required reading and other learning resources/tools
1. Nefedov Yu. M. Methods of optimization in examples and problems: textbook / Yu. M. Nefedov, T. Yu. Balytska. - Київ: Кондор, 2011. - 324 с. 2. Zaichenko YP Research operations. Textbook / Yu. P. Zaichenko. - 7th ed., Reworked. and add. - Kyiv: Slovo Publishing House, 2006. - 816 p. 3. Dziuban IY Methods of research operations / IY Dziuban, OL Zhirov, OG Okhrimenko. - Kyiv: IPC "Polytechnic Publishing House", 2005. - 108 p. 4. Nakonechny SI Mathematical programming: textbook. way. / SI Nakonechny, SS Savina. - Kyiv: KNEU, 2003. - 452 pp. Research of operations in economics: textbook / ed. IK Fedorenko, OI Chernyak. - Kyiv: Knowledge, 2007. - 558 p. - (Higher education of the XXI century). 5. Hamdi. A. Taha. Introduction to Operations Research, 10th Edition. - M .: Williams, 2016. 912 p. 6. Hamdy A. Taha, Operations Research: An Introduction, 10th Edition,, University of Arkansas, © 2017, Pearson 7. Yu.D. Popov, VI Tyuptya, VI Shevchenko “Optimization methods”, K., 2000
Planned learning activities and teaching methods
Lectures, practice work, independent work, recommended literature processing, 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

Roman Ya. Yakymiv
Operations Research
Faculty of Computer Science and Cybernetics
Alexander M. Iksanov
Operations Research
Faculty of Computer Science and Cybernetics
Andrii V. Zavorotynskyi
Operations Research
Faculty of Computer Science and Cybernetics
Oksana A. Braganets
Operations Research
Faculty of Computer Science and Cybernetics
Inna S. Rybalko
Operations Research
Faculty of Computer Science and Cybernetics