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Бакалавриат 2019/2020

Методы принятия решений

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Направление: 38.03.04. Государственное и муниципальное управление
Когда читается: 3-й курс, 1, 2 модуль
Формат изучения: с онлайн-курсом
Язык: английский
Кредиты: 4
Контактные часы: 48

Course Syllabus

Abstract

The course includes main notions and stages of decision making, relevant mathematical models and methods, namely, linear and nonlinear programming, multi-objective and dynamical optimization methods, game considerations and their use in applied problems. Дистанционное обучение производится на платформах MS Teams, Webinar и Zoom. Ссылка на конкретные занятия заранее высылается преподавателем по почте.
Learning Objectives

Learning Objectives

  • To familiarize students with basic concepts, models and methods of decision making.
Expected Learning Outcomes

Expected Learning Outcomes

  • 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
Course Contents

Course Contents

  • Introduction
    Participants and stages of decision making (DM). Mathematical models and methods in DM.
  • Multicriterial Decision Making (MCDM)
    Vectorial criteria, decision and criterial spaces, multicriterial preferences. Pareto optimality. Linear convolution method, threshold aggregation. An evaluation of the efficiency of administrative reform in Russia.
  • Network analysis
    Centrality in networks. Other characteristics of networks. Different applications – international conflicts, migration, trade, etc.
  • Power distribution in international organizations
    The concept of power. Shapley-Shubik and Banzhaf indices. Other power indices. Power indices based on the agents’ preferences to coalesce. Power distribution in IMF, Russian commercial banks.
  • Double-sided matchings
    Preferences of agents. Gale-Shapley algorithm. Distribution of works among workers.
  • Fair division
    Criteria for fair division. Adjusted winner procedure. Other procedures. An allocation of disputable zones in Arctic.
  • Game-theoretic models
    Two-person games. Dominant strategies. The concept of equilibrium. Nash equilibria in pure strategies. Mixed strategies. Nash equilibria in mixed strategies. Focal equilibria. Several applications.
Assessment Elements

Assessment Elements

  • non-blocking homework
  • non-blocking test 1
  • non-blocking test 2
  • non-blocking final exam
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    0.5 * final exam + 0.1 * homework + 0.2 * test 1 + 0.2 * test 2
Bibliography

Bibliography

Recommended Core Bibliography

  • Aleskerov F., Bouyssou D., Monjardet B. ‘Utility Maximization, Choice and Preference’, Springer Verlag, Berlin, 2007

Recommended Additional Bibliography

  • Osborne, M. J. (2009). An introduction to game theory / Martin J. Osborne. New York [u.a.]: Oxford Univ. Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.324093616