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Бакалавриат 2025/2026

Методы принятия решений

Когда читается: 3-й курс, 1, 2 модуль
Онлайн-часы: 8
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 4
Контактные часы: 52

Course Syllabus

Abstract

The course presents fundamental concepts, models and different applications in decision-making, with a focus on formal methods and mathematical modeling. It examines both classical and modern frameworks, including the analysis and optimization of individual and collective choices. The program covers a wide range of models, including multicriterial decision-making, network analysis, power distribution in collective bodies, matching theory, and fair division. Special attention is given to game-theoretic approaches, methods of efficiency evaluation, and rules of collective choice and voting. Theoretical results are consistently illustrated by applications to real-world cases in economics, politics, and social systems. The course aims to provide students with a comprehensive understanding of how decision-making models are constructed and applied, to develop the ability to select rational strategies in complex environments, and to form analytical skills for evaluating and comparing different mechanisms of choice.
Learning Objectives

Learning Objectives

  • Know principles of mathematical models construction in decision analysis
  • Be able to choose rational options in practical decision-making problems
  • Have skills in analysis of game-theoretic models
Expected Learning Outcomes

Expected Learning Outcomes

  • 1 - Know principles of mathematical models construction in decision analysis
  • 2 - Be able to choose rational options in practical decision-making problems
  • 3 - Have skills in analysis of game-theoretic models
Course Contents

Course Contents

  • Topic 1. Introduction.
  • Topic 2. Multicriterial Decision Making (MCDM).
  • Topic 3. Voting rules and collective choice.
  • Topic 4. Power distribution in international organizations.
  • Topic 5. Network analysis.
  • Topic 6. Double-sided matchings.
  • Topic 7. Fair division.
  • Topic 8. Game-theoretic models.
  • Topic 9. Decision-Making in Disaster Management.
  • Topic 10. Data Envelopment Analysis.
Assessment Elements

Assessment Elements

  • non-blocking Homework
    As part of the course requirements, students are assigned homework tasks during classes, accompanied by a detailed explanation of the conditions and requirements for their completion. The deadline for submission is one week from the date of assignment. Resubmission of homework tasks is not permitted. The final grade for this assessment component is calculated as the arithmetic mean of all homework grades obtained. Failure to submit or late submission of a homework task results in the assignment of a grade of 0 points for that task.
  • non-blocking Test 1
    Test 1 shall be conducted in written form under in-class conditions. The use of any supplementary or auxiliary materials during the test is strictly prohibited. Retaking the test is not permitted.
  • non-blocking Test 2
    Test 2 shall be conducted in written form under in-class conditions. The use of any supplementary or auxiliary materials during the test is strictly prohibited. Retaking the test is not permitted. In the event that certain course topics cannot be included in Test 1, the corresponding tasks may be transferred to Test 2.
  • non-blocking Exam
    Exam shall be conducted in written form under in-class conditions. The use of any supplementary or auxiliary materials during the test is strictly prohibited.
Interim Assessment

Interim Assessment

  • 2025/2026 2nd module
    0.5 * Exam + 0.05 * Homework + 0.05 * Homework + 0.2 * Test 1 + 0.2 * Test 2
Bibliography

Bibliography

Recommended Core Bibliography

  • An introduction to game theory, Osborne, M. J., 2009
  • Utility maximization, choice and preference : with 49 figures and 28 tables, Aleskerov, F., 2007

Recommended Additional Bibliography

  • Theory of choice, Aizerman, M., 1995

Authors

  • Miachin Aleksei Leonidovich
  • ALESKEROV FUAD TAGI OGLY