DRL034 Strategic Decision-Making in Logistics (Autumn 2024)

About the course

This course explores strategic decision-making in supply chains using game theory as the primary framework. Widely employed across various disciplines like economics, politics, and biology, game theory offers an analytical framework for addressing numerous logistical and supply chain challenges. To name a few examples: buyer-supplier negotiations, inventory games, routing games, collaborative planning and coordination among different entities in a supply chain. Through the lens of game-theoretic models and principles, students will gain insights into strategic behaviour and coordination mechanisms in supply networks and acquire tools to analyse logistics challenges from a strategic perspective.

The course is structured in the following way:

• The morning sessions present the foundational game-theoretic models and principles.

• The afternoon sessions explore more advanced topics, based on the academic research and case studies.

The topics covered in the course:

1. The main theoretical concepts of game theory: normal-form games and extensive-form games, main solution concepts (e.g. Nash equilibrium, Pareto optimality, Subgame perfect Nash equilibrium etc), bargaining games, coalitional games (cost allocation methods, core).

2. An overview of the classical “logistics” games: travelling salesman game, inventory control games, facility location games, network design games, and routing games.

3. An introduction to market equilibrium modelling and mixed complementarity problems.

4. Cooperative games with uncertainty: interval games and dynamic games.

5. An introduction to incomplete information games and mechanism design.

The course is connected to the following study programs

• Philosophiae Doctor in Logistics (PhD)

Recommended requirements

• Accepted as a PhD student

• Basic math skills and some understanding of probability theory

• Some knowledge of microeconomics might be an advantage.

The student's learning outcomes after completing the course

 

• Students will develop an in-depth understanding of main theoretical concepts and principles of game theory (e.g. strategic games, strategies, Nash equilibrium; extensive form games, backward induction, subgame perfection; cooperative games, core, allocation rules).

• Students will acquire an overview of the existing extensions of classical game-theoretic concepts to problems within logistics and supply chain management, such as routing games, network games, cost allocations in supply chains under uncertainty.

• Students should be able to identify environments with strategic interactions and structure real-world problems in supply chain management and logistics as games, using the formal language of game theory.

• Students will develop critical approach to the research in applied game theory and be able to evaluate the effectiveness of different game-theoretical models in addressing logistics challenges.

• Students will be able to contribute to the research on applications of game-theoretic concepts to logistics and supply chain management.

Forms of teaching and learning

One week of teaching:

1. The morning sessions (three hours, Monday – Friday) together with MSc students – the seminar LOG904-114 Game Theory Applied in Logistics.

2. The afternoon sessions (three hours, Monday – Friday) – workshops only for the PhD students, involving lecturing on advanced topics, discussions, and student presentations.

Coursework requirements - conditions for taking the exam

All lectures and workshops must be attended. One presentation during the course week.

Examination

Submission of a course paper within four weeks after the course.

Syllabus

• Binmore, K. (2007). Playing for real: a text on game theory. Oxford University Press, New York.

• Leyton-Brown, K., & Shoham, Y. (2008). Essentials of game theory: A concise multidisciplinary introduction. Synthesis Lectures on Artificial Intelligence and Machine Learning, 2(1).

• Gabriel, S. A., Conejo, A. J., Fuller, J. D., Hobbs, B. F., & Ruiz, C. (2012). Complementarity modelling in energy markets, ser. International series in operations research & management science.

• Peleg, B., & Sudhölter, P. (2007). Introduction to the theory of cooperative games (Vol. 34). Springer Science & Business Media.

• Research papers: TBA