Problems of non-classic optimization
Course: Applied mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Problems of non-classic optimization
        
    
            Code
        
        
            ННД.13
        
    
            Module type 
        
        
            Обов’язкова дисципліна для ОП
        
    
            Educational cycle
        
        
            Second
        
    
            Year of study when the component is delivered
        
        
            2021/2022
        
    
            Semester/trimester when the component is delivered
        
        
            1 Semester
        
    
            Number of ECTS credits allocated
        
        
            6
        
    
            Learning outcomes
        
        
            PLO2. Understanding of the principles and methods of analysis and evaluation of the range of tasks that contribute to the further development of effective use of information resources. PLO6. Be able to design and use existing data integration tools, and process data stored in different systems.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            To successfully study the discipline of "Non-classical optimization problems", a student must meet the following requirements: 1. Knowledge: Theoretical foundations and methods of research of complex systems using methods of equations of mathematical physics and mathematical modeling. Principles of mathematical modeling of complex processes. 2. Skill: Solve basic problems of the theory of differential equations and mathematical physics. Create numerical methods for solving mathematical physics equations. Formulate optimization problems for solving practical problems. Apply methods of mathematical and computer modeling to study systems and build mathematical models. 3. Ownership: Programming skills. Skills in building, analyzing, and applying mathematical models when solving applied computer modeling problems.
        
    
            Course content
        
        
            The purpose of the discipline is to increase the level of fundamental mathematical training, and to familiarize with the main provisions of modern optimized computational methods in the problems of mathematical modeling of complex processes using singular integral equations.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            2. Dovgiy S.O., Liashko S.I., Cherniy D.I. Alhorytmy metodu dyskretnykh osoblyvostei dlia obchysliuvalnykh tekhnolohii. // Kybernetyka y systemnыi analyz. 2017, № 6. pp. 147-159. 3. Matviienko V.T., Metody optymizatsii parametrychnykh system./ Volodymyr T. Matviienko, Volodymyr V. Pichkur, Dmytro I. Cherniy // Zhurnal obchysliuvalnoi ta prykladnoi matematyky., No 1 V(135) 2021. pp.151-157. 5. I.K.Lifanov, L.N.Poltavskii, G.M.Vainikko. Hypersingular Integral Equations And Their Applications. – London, New York, Washington D.C.: «Chapman &Hall/CRC». – 2001. – 396 p.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, laboratory classes, independent work.
        
    
            Assessment methods and criteria
        
        
            The maximum number of points that can be obtained by a student is 100 points. 1. Test work No 1: 30/18 points. 2. Test work No 2: 30/18 points. 3. Current assessment: 40/24 points. Final assessment in the form of a test: According to paragraphs 4.6.1 and 7.1.5 of "Regulations on the organization of the educational process at the Taras Shevchenko National University of Kyiv" credit is given based on current control (see semester evaluation) as the sum of grades/points for all successfully evaluated learning outcomes; grades below the minimum threshold level are not added to the final grade. All students are allowed to take the test.
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Vasyl
                    Vasylovych
                    Begun
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
                    Vasyl
                    Serhiiovych
                    Mostovyi
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics
                    
                
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics