“…The authors, therefore, proposed an improved exact approach based on Benders decomposition [19] supported by a heuristic and compared it to the standard MILP approach on problem instances with up to 100 EVs and 1600 reservations. Later, Limmer et al [20] proposed a hybrid evolutionary approach for the EV fleet scheduling problem, where the assignment of EVs to reservations is optimized with an evolutionary algorithm, and in the fitness evaluation, linear programming is used to optimize a charging plan for the fixed reservation assignment. Furthermore, the authors described two surrogate-based variants of the approach.…”