2019 Advanced Topics in Mathematical Economics

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Academic unit or major
Graduate major in Industrial Engineering and Economics
Instructor(s)
Shioura Akiyoshi 
Course component(s)
Lecture
Day/Period(Room No.)
Tue3-4(W9-508)  Fri3-4(W9-508)  
Group
-
Course number
IEE.B433
Credits
2
Academic year
2019
Offered quarter
3Q
Syllabus updated
2019/3/18
Lecture notes updated
2019/10/16
Language used
Japanese
Access Index

Course description and aims

We discuss an auction model with many indivisible (discrete) goods. It is known that an optimal allocation of goods as well as equilibrium prices can be computed by algorithms (protocols) called iterative auctions. In this lecture, we review various iterative auctions and investigate them from the viewpoint of discrete optimization. In particular, we explain the concept of gross-substitutes valuation, which plays a crucial role in the auction, and show the connectin with discrete concavity.

This lecture aims to enable students to understand the power of theoretical results in discrete optimization in application to auction theory in economics.

Student learning outcomes

By the end of this course, students will be able to do the following:
(1) explain the auction model with indivisible goods,
(2) understand the concept of gross-substitutes condition and its properties,
(3) explain how iterative auctions find equilbrium prices,
(4) understand the connection between iterative auctions and optimization algorithms.

Keywords

auction, discrete optimization, equilibrium, algorithm

Competencies that will be developed

Intercultural skills Communication skills Specialist skills Critical thinking skills Practical and/or problem-solving skills
- - - -

Class flow

In each class we give a lecture in the first half and then assign some exercise problems in the last half.

Course schedule/Required learning

  Course schedule Required learning
Class 1 overview of the lecture Details will be given in each lecture.
Class 2 Review of shortest path problem (1)
Class 3 Review of shortest path problem (2)
Class 4 Matching problem on a bipartite graph (1)
Class 5 Matching problem on a bipartite graph (2)
Class 6 optimality condition for maximum matching
Class 7 Maximum-weight matching problem
Class 8 relationship between maximum-weight matching and equilibrium allocation
Class 9 algorithm for computing an equilibrium approximately
Class 10 algorithm for computing an equilibrium exactly
Class 11 multi-demand model and equilibrium
Class 12 gross substitutes property for valuation functions
Class 13 algorithm for computing an equilibrium approximately
Class 14 algorithm for computing an equilibrium exactly
Class 15 summary of the lecture

Textbook(s)

None.

Reference books, course materials, etc.

Related Paper:
K. Murota, A. Shioura, and Z. Yang: Time bounds for iterative auctions: a unified approach by discrete convex analysis, Technical Report METR 2014-39, University of Tokyo, December 2014.

Related Book:
K. Murota: Discrete Convex Analysis, SIAM, 2003

Assessment criteria and methods

Evaluation based on reports and exams

Related courses

  • IEE.B337 : Mathematical Economics
  • IEE.A206 : Operations Research
  • IEE.A330 : Advanced Operations Research
  • IEE.B401 : Advanced Microeconomics
  • IEE.B403 : Advanced Noncooperative Game Theory

Prerequisites (i.e., required knowledge, skills, courses, etc.)

It is desirable to have enough knowledge on the contents of the lecture "Mathematical Economics (IEE.B337)".

Contact information (e-mail and phone)    Notice : Please replace from "[at]" to "@"(half-width character).

shioura.a.aa[at]m.titech.ac.jp

Office hours

Any time. Prior appointment by e-mail is desirable.

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