This project studies contract design for combinatorial optimization problems. The core setting is a principal-agent interaction in infrastructure networks: the user side aims for high network utility, while the operator side mainly minimizes operating costs. We model this tension as a bilevel optimization problem with linear contracts.

Methodologically, we combine combinatorial optimization, parametric flow techniques, approximation, and duality-based methods. The goal is to develop computationally efficient and mathematically robust contract mechanisms for real-world network applications in mobility and energy.

WP1: Efficient and approximate solution methods for the bilevel flow problem under linear contracts.

WP2: Extension to potential-based flows that capture physical network effects (e.g., gas, electricity, traffic).

WP3: A general contract-design framework for combinatorial lower level decisions, centered on Lagrangian duality and critical parameter values.

The project contributes to AA3 (Mobility) and AA4 (Energy) by developing mathematical tools for regulated and unbundled infrastructure networks, and strengthens the interface between optimization and economic sciences.