On the optimization of pit stop strategies via dynamic programming

Pit stops are a key element of racing strategy in several motor sports. Typically, these involve decisions such as which laps to stop, and type tire, three possible compounds, set at each stops. There factors that increase the complexity task: impact lap times depending on tire compound, wear tires, unexpected events track safety cars weather, among others. This work presents Dynamic Programming formulation addresses pit-stop problem order optimize changes minimize total race time. We show relative performance optimal strategies for starting with tires different compounds yellow-flag scenarios. Then, we extend Program (DP) Stochastic (SDP) incorporates random yellow flags or rainy weather. able visualize compare obtained models SDP solution, compared DP tends delay pit benefit from flag. Finally, outperforms DP, especially races likely be waved more frequently.