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System Analysis and Operations Research
Major: Distributed Information Systems and Technologies
Code of subject: 6.126.03.O.031
Credits: 5.00
Department: Information Systems and Networks
Lecturer: Candidate of Technical Sciences, Associate Professor Shestakevych Tetiana
Semester: 5 семестр
Mode of study: денна
Завдання: Studying the academic discipline involves the formation of competencies in students:
integral competence:
The ability to solve complex specialized tasks and practical problems of system analysis in professional activities or in the learning process, which involve the application of theoretical provisions and methods of system analysis and information technologies and are characterized by the complexity and uncertainty of conditions.
general competencies:
KZ 1. The ability to abstract thinking, analysis and synthesis.
KZ 2. The ability to apply knowledge in practical situations.
KZ 5. The ability to learn and master modern knowledge.
KZ 6. The ability to search, process and generalize information from various sources.
KZ 7. The ability to develop and manage projects.
KZ 8. The ability to evaluate and ensure the quality of work performed.
KZ10. The ability to preserve and multiply the moral, cultural, scientific values ??and achievements of society based on understanding the history and patterns of the development of the subject area, its place in the general system of knowledge about nature and society and in the development of society, technology and technology, to use various types and forms of physical activity for active recreation and leading a healthy lifestyle.
Special (professional, subject) competencies:
KS 1. The ability to analyze the design or functioning object and its subject area.
KS 2. The ability to apply standards in the field of information systems and technologies when developing functional profiles, building and integrating systems, products, services and elements of the organization's infrastructure.
KS 4. The ability to design, develop and use means of implementing information systems, technologies and infocommunications (methodological, informational, algorithmic, technical, software and others).
KS 6. Ability to use modern information systems and technologies (production, decision support, data mining, etc.), cybersecurity methodologies and techniques when performing functional tasks and duties.
KS 10. Ability to select, design, deploy, integrate, manage, administer and maintain information systems, technologies and infocommunications, services and infrastructure of the organization.
KS 11. Ability to analyze, synthesize and optimize information systems and technologies using mathematical models and methods.
KS13. Ability to conduct computational experiments, compare the results of experimental data and the obtained solutions.
Learning outcomes: After successfully completing the course, the student will know:
• Theoretical foundations of systems analysis, its methodology and the main stages of studying complex systems.
• Classification and principles of building models, including mathematical, graphical and hierarchical models.
• Key tasks of operations research, such as the transportation problem, the destination problem, the backpack problem and the traveling salesman problem.
• Methods of multi-criteria analysis and decision-making, in particular the analytic hierarchy process (AHP) and classical criteria (Wald, Savage, Hurwitz).
• Possibilities and limitations of using artificial intelligence tools to solve problems of systems analysis and operations research.
The student will be able to:
• Form mathematical models for real problems, defining variables, constraints and the objective function.
• Analyze the relationships between system parameters using influence matrices and dependency graphs.
• Identify key drivers and central nodes in complex systems using cause-and-effect graphs.
• Use multi-criteria analysis methods to evaluate and compare alternative solutions.
• Conduct scenario analysis and make informed decisions under uncertainty.
• Critically evaluate and verify results obtained using AI tools, formulate queries correctly, and identify inaccuracies.
PR2. Apply knowledge of fundamental and natural sciences, systems analysis and modeling technologies, standard algorithms and discrete analysis when solving problems of designing and using information systems and technologies.
PR4. Conduct a system analysis of design objects and justify the choice of structure, algorithms and methods of information transmission in information systems and technologies.
PR9. Carry out a system analysis of the architecture of the enterprise and its IT infrastructure, develop and improve its element base and structure.
Required prior and related subjects: Databases
Special programming languages
Summary of the subject: The discipline "Systems Analysis and Operations Research" is dedicated to the study of theoretical foundations and practical methods of analyzing complex systems in order to improve the efficiency of management and support decision-making. The course covers the methodology of the systems approach, ranging from the formation of mathematical models and identification of key parameters, to multifactor analysis and evaluation of alternative scenarios.
Students acquire skills in the application of modern tools, such as matrix and graph analysis, multi-criteria choice methods (AHP), as well as classical criteria for decision-making under uncertainty (Wald, Savage, Hurwitz).
The course integrates traditional methods of operations research with the innovative use of artificial intelligence as an auxiliary tool. Special attention is focused on the development of critical thinking: students learn to verify the results obtained using AI, justify their decisions and identify the limitations of technological tools, which is fundamental for specialists in the field of systems analysis.
Опис: Topic 1. Fundamentals of systems analysis, operations research and modeling standards
Systems analysis as a methodology for studying complex objects and their subject areas.
Operations research as a tool for decision-making. Modeling methods, types of models and stages of systems analysis.
International standards and notations (ISO/IEC, UML, IDEF, BPMN) for describing subject areas and systems integration.
Topic 2. Structural models and optimization methods in systems analysis
Graph models for describing the structure and relationships in systems.
Application of the transportation problem and the assignment problem for optimization.
Methodologies of structural modeling and systems integration (DFD, BPMN). The transportation problem and the assignment problem as examples of optimization problems on graphs.
Topic 3. Cause-and-effect analysis and strategic management of systems
Methods for identifying drivers and dependent outcomes.
Construction of graphs of cause-and-effect relationships and search for critical nodes.
Classical operations research problems (backpack, traveling salesman) as a tool for strategic analysis and decision-making.
Topic 4. Multi-criteria optimization methods and computational experiments
Mathematical models for selecting optimal solutions in multi-criteria problems.
Analytical hierarchy process (AHP) as a tool for justifying choices.
Linear programming and graphical solution method.
Fundamentals of game theory and analysis of strategic conflicts.
Computational experiments and laboratory studies using the Multi-Criteria Evaluation (MCE) method.
Topic 5. Analysis of decisions under risk, uncertainty and simulation modeling
Decision-making methods with complete and incomplete information.
Classical criteria (Wald, Savage, Hurwitz).
Construction of a decision matrix and scenario analysis.
Simulation modeling as a means of testing the effectiveness of strategies under risk.
Topic 6. Modern intelligent technologies, cybersecurity and the life cycle of information systems
Artificial intelligence, Big Data, machine learning and cloud technologies as tools for system analysis.
Ethical aspects and risks of using AI in operations research.
Fundamentals of cybersecurity and data protection in the process of modeling and analyzing systems.
The life cycle of information systems: design, deployment, administration and maintenance.
Assessment methods and criteria: Knowledge diagnostics is carried out by evaluating completed laboratory work and examination control (written and oral components) in the form of test questions.
Forms and methods of controlling students' independent work:
• written survey,
• checking notes based on video lecture materials.
Критерії оцінювання результатів навчання: The procedure and criteria for assigning points and grades
The assessment of the knowledge of education seekers is based on the completion of tasks within the framework of laboratory classes (current control) and the performance of examination control.
It is planned to perform 5 laboratory works per semester, the maximum number of points is 45. The defense of all laboratory works is a mandatory condition for admission to the exam. Distribution of points and assessment criteria in the RP.
Порядок та критерії виставляння балів та оцінок: 100-88 points - certified with an “excellent” grade - High level: the student demonstrates an in-depth mastery of the conceptual and categorical apparatus of the discipline, systematic knowledge, skills and abilities of their practical application. The mastered knowledge, skills and abilities provide the ability to independently formulate goals and organize learning activities, search and find solutions in non-standard, atypical educational and professional situations. The applicant demonstrates the ability to make generalizations based on critical analysis of factual material, ideas, theories and concepts, to formulate conclusions based on them. His/her activity is based on interest and motivation for self-development, continuous professional development, independent research activities, implemented with the support and guidance of the teacher. 87-71 points - certified with a grade of “good” - Sufficient level: involves mastery of the conceptual and categorical apparatus of the discipline at an advanced level, conscious use of knowledge, skills and abilities to reveal the essence of the issue. Possession of a partially structured set of knowledge provides the ability to apply it in familiar educational and professional situations. Aware of the specifics of tasks and learning situations, the student demonstrates the ability to search for and choose their solution according to the given sample, to argue for the use of a particular method of solving the problem. Their activities are based on interest and motivation for self-development and continuous professional development. 70-50 points - certified with a grade of “satisfactory” - Satisfactory level: outlines the mastery of the conceptual and categorical apparatus of the discipline at the average level, partial awareness of educational and professional tasks, problems and situations, knowledge of ways to solve typical problems and tasks. The applicant demonstrates an average level of skills and abilities to apply knowledge in practice, and solving problems requires assistance, support from a model. The basis of learning activities is situational and heuristic, dominated by motives of duty, unconscious use of opportunities for self-development. 49-00 points - certified with a grade of “unsatisfactory” - Unsatisfactory level: indicates an elementary mastery of the conceptual and categorical apparatus of the discipline, a general understanding of the content of the educational material, partial use of knowledge, skills and abilities. The basis of learning activities is situational and pragmatic interest.
Recommended books: 1. Selected sections of multi-criteria optimization: methodological recommendations for performing control and laboratory work for students of the Faculty of Mathematics / Developer: N. E. Kondruk. – Uzhgorod: UzhNu, 2015. – 56 p.
2. Dyvak M.P. Identification of discrete models of dynamic systems with interval data: monograph / M.P. Dyvak, N.P. Porplytsia, T.M. Dyvak. – Ternopil: VPC “Economic Thought TNEU”, 2018. – 220 p.
3. Katrenko A. V. Operations research: textbook – 3rd ed., ed. – Lviv: “Magnolia-2006”, 2024. – 350 p.
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