This award intends to improve infrastructure operations by supporting research on new economic mechanisms for markets with discrete decisions. A prominent example is unit commitment, which schedules when each fuel-burning generator in a power system is on and off. Startup and shutdown account for a significant portion of the cost of generation, and they are binary decisions because a generator can only be on or off. The discreteness of unit commitment undermines standard economic mechanisms. In particular, resulting prices are generally too low, so that system operators must make out-of-market uplift payments to keep generators profitable. In general, discreteness such as this can create negative incentives in markets, leading to inefficient investment and decision-making. Research to be completed in association with this project intends to offer a new approach to designing pricing mechanisms in discrete markets, with the focus on power systems and electric vehicle charging. It will produce new tools and deepen understanding of tradeoffs in discrete markets. The project team has expertise in power systems and transportation, optimization, and market design, and will train graduate students with the multidisciplinary perspectives needed for this project. This project will investigate the use of copositive programming as a tool for designing economic mechanisms for discrete markets. The approach is based on a fundamental result from Burer (2009), which establishes that a mix