A NN is trained to approximate the cut locations for a single step time-horizon of the LS method on each training configuration. Due to the fixed length of the input vector (64 segment endpoints), each initial condition can be mixed 𝑁 = 31 times (32 segments of each color). We refer to NNs trained using 𝑇 initial conditions and their 31 LS method descendants as NN 𝑇 for 100 (NN 100 ), 1 000 (NN 1k ), and 10 000 (NN 10k ) evenly spaced initial conditions with respect to 𝑏. NNs trained using 𝑇 = 1 000 initial conditions with a random (uniformly distributed) sampling of 0 < 𝑏 < 1 are referred to as NN rand . To maintain a constant computational training effort, each of these networks is trained using 10