Optimization, Learning, and Market Design

Market design uses economic theory, mathematical optimization, systems design, experiments, and empirical analysis to design market rules and institutions. Fundamentally, market design asks how the design of the rules and regulations of a market affects the functioning and outcomes of that market. The study includes auction markets, but also markets without money such as matching markets, which found application in the assignment of students to courses or in school choice programs. We are contributing to various strands in this literature including optimization in market design, equilibrium computation, mechanism design, and experiments. Current team members and projects can be found below. In the past we have actively contributed to the following application domains:

  • Electricity market design (e.g. our contributions to the SynErgie project). 
  • Spectrum auction design (e.g. Handbook of Spectrum Auction Design) 
  • Design of environmental markets (e.g., the implementation of a large scale combinatorial exchange for the trading of catch shares in Australia, PNAS articlevideo).
  • Design of a course assignment mechanism (e.g. the matching system used at the Technical University of Munich)
  • Design of procurement auctions and transportation tenders with industry partners (various industry projects in transportation and procurement, winner of the Siemens SCM Olympics).


We have open-sourced several software packages in the past. The most recent software we released provides the code for our NPGA equilibrium learner, which finds Bayesian Nash equilibria in auction games.

  • M. Bichler, M. Fichtl, S. Heidekrüger, N. Kohring, and P. Sutterer. Learning equilibria in symmetric auction games using artificial neural networksNature Machine Intelligence, 3:687–695, August 2021. [ DOI | link | pdf ] 

Current Team Members

Prof. Martin Bichler, Eleni Batziou, Markus Ewert, Max Fichtl, Stefan Heidekrüger, Nils Kohring, Johannes Knörr, Fabian Pieroth, Matthias Oberlechner, Gregor Schwarz, Donghao Zhu

DFG Research Training Group AdONE

Advanced Optimization in a Networked Economy

The PhD program AdONE is jointly hosted by the Department of Computer Science, and Department of Mathematics and the School of Management, at TUM. We are funded by the German Science Foundation (DFG) as a "Research Training Group". Our work is at the intersection of mathematicscomputer science, and management science, driven by exciting applications such as airport operations, auction mechanisms for network procurement, autonomous mobility, carsharing systems, production planning, vehicle routing, warehousing & e-commerce.

Kopernicus Project SynErgie

Electricity Market Design for the Future

The project aims to design electricity markets for a future with large amounts of renewable energy sources. The energy transition requires us to rethink mathematical models for efficient dispatch and pricing of electricity on wholesale markets. 

Koselleck Project (German Research Foundation)

Designing Non-Convex Markets

This project develops mathematical models for non-convex markets as they can be found in spectrum sales, the trading of fishery access rights, in electricity markets, etc.