The transfer of trailers between arrival areas and loading/unloading docks in logistics warehouses traditionally requires specialized tractors operated by qualified drivers. Faced with the growing shortage of workforce for these activities, the automation of these operations through the adoption of autonomous electric tractors emerges as a strategic solution to ensure the continuity and reliability of logistics flows~\cite{benvco2025automated}. Therefore, we address a complex scheduling problem that combines several decision dimensions. We formulate it as an extended \textit{Flexible Job Shop Scheduling Problem}, where tractors are mobile machines with limited energy capacity (batteries). The problem integrates four interdependent decision levels: (1) flexible assignment of tractors to transportation operations, (2) temporal sequencing ensuring precedence and dock capacity constraints, (3) spatial allocation of trailers to arrival locations, docks, and departure locations, and (4) battery recharging planning under station capacity constraints. The main contribution lies in establishing an integrated MILP formulation that simultaneously captures the dimensions of flexible scheduling, spatially dependent routing, energy management, and resource allocation. We also propose a resolution strategy, a linear relaxation for bound computation, and metaheuristics adapted to the problem structure.