A simulation framework for Formula 1 race strategy based on pit-stop optimization

In modern Formula 1, strict regulations and highly optimized cars limit performance gains through hardware, increasing the importance of strategic decision-making. This work tackles the problem of computing a race strategy that minimizes total race time by jointly optimizing tyre stints, compound selection, fuel load, and Energy Recovery System (ERS) deployment. We present a high-performance simulation framework based on the solution of an optimization model, designed for fast and reliable trackside use. The system considers discrete stint allocation with ERS management and includes real-time visualization tools for drivers and race engineers. Validation uses semi-realistic data from a Formula 1 simulator and is further refined with a professional simulation platform. Benchmarking shows improved fidelity and performance compared to existing models.