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Fundamentals of Network Analysis for Econometrics and Operations Research

2019-2020

Course Objective

After completion of the course, the student is able to
• reason about networks in a unified abstract way;
• recognize problems as network problems;
• construct mathematical models for basic network problems, specifically
for problems in network optimization and games on networks;
• adapt simple algorithms for variations of network optimization
problems;
• apply noncooperative game tools to understand strategic behavior of
agents in networks;
• apply cooperative game theoretic tools for solving allocation
problems on networks.

Course Content

Game theory and operations research (OR) provide methods for network
analysis. Noncooperative game theory studies how rational agents make
strategic decisions. Cooperative game theory is often used as a decision
support system in valuation problems. OR provides methods and algorithms
for computing optimal solutions. In this minor, these techniques will be
used in network optimization problems. To prepare you for that, this
course discusses basic methods and models of game theory and OR
networks.

The course introduces the student to the following topics:

• Elementary graph theory, introducing the basic mathematical concepts
used to uniformly model most problems concerning networks;
• An algorithmic view on network optimization, while introducing basic
optimization problems like shortest paths, minimum spanning tree, and
max flow ;
• Basic network properties like large components and short diameters;
• Introduction to noncooperative games, including normal games,
extensive form games, dominant strategies, Nash equilibrium, and subgame
perfect equilibrium;
• Introduction to cooperative games, including transferable utility
games, the Core, and the Shapley value;
• Applications of games to network analysis.

IMPORTANT: This module introduces students to the fundamentals of
network analysis from the perspectives of (econometrics and) operations
research. It is required for students with a background in either
economics or business, whereas students with a background in
(econometrics and) operations research should NOT attend this module.

Teaching Methods

2 hours of lectures and 2 hours of tutorial per week

Method of Assessment

Written exam (75%), Tutorial assignments (25%)

Entry Requirements

Basic mathematics courses, including basic linear algebra and basic
calculus

Lecture notes

General Information

Course Code E_EBE3_FEOR 6 EC P1 300 English School of Business and Economics prof. dr. J.R. van den Brink prof. dr. J.R. van den Brink prof. dr. J.R. van den Brink dr. R.D. Nobel

Practical Information

You cannot register for this course yourself; your faculty's education office carries out registration

Last-minute registration is available for this course.

Teaching Methods Study Group, Lecture
Target audiences

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