Decomposing methods of discrete optimization
Course: System Analysis
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Decomposing methods of discrete optimization
        
    
            Code
        
        
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2022/2023
        
    
            Semester/trimester when the component is delivered
        
        
            7 Semester
        
    
            Number of ECTS credits allocated
        
        
            2
        
    
            Learning outcomes
        
        
            Know the history of the formation and development of discrete optimization; basic concepts of discrete optimization.
Know modern development trends, scientific and applied achievements of discrete optimization.
Know modern approaches, optimization methods, computer technologies and tools for solving current scientific problems of discrete optimization.
Know the theoretical methods of studying the complexity and speed of computational algorithms.
To be able to formulate the general methodological basis of own scientific research from new research positions, to realize its urgency, the purpose and value for development of discrete optimization.
Be able to develop and apply methods of discrete optimization for mathematical modeling and optimization of scientific and technical, economic, environmental and social processes and systems.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            1. Know: the material of standard university courses in mathematical analysis, linear algebra, operations research and decision theory, probability theory, graph theory, discrete optimization using modern computing resources; program in one of the current programming languages.
2. Be able to: develop, analyze and apply decomposition algorithms to solve problems and applied problems, implement algorithms to program in one of the modern programming languages.
        
    
            Course content
        
        
            The discipline "Problems of cryptography, optimization and risk analysis" belongs to the list of disciplines of choice by blocks. The subject of module 2 "Decomposition methods of discrete optimization" of the discipline are current problems of discrete optimization, relating to the basic principles of development of mathematical methods of decomposition to solve complex problems of discrete optimization. It provides acquaintance, deepening and improvement of knowledge, which is an element of fundamental mathematical training of students, and which can be used in the practical application of models and methods of discrete optimization in solving complex problems of optimal design, management of economic and technical facilities and systems. as well as in the implementation of research projects. 
Taught in the 7th semester, 30 hours. (2 ECTS credit), of which seminars - 16 hours, independent work - 14 hours. There are 2 substantive parts and a test.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            2. Sergienko IV Informatics in Ukraine: formation, development of the problem. K .: Nauk. opinion, 1999. 354 p.
7. Semenova NV, Kolechkina LM Vector problems of discrete optimization on combinatorial sets: research methods and solutions. Kyiv: Nauk. opinion,
2009. 266 p.
        
    
            Planned learning activities and teaching methods
        
        
            Lecture, individual work
        
    
            Assessment methods and criteria
        
        
            Current assessment, control work, credit
        
    
            Language of instruction
        
        
            Ukrainian
        
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