This paper develops a computationally efficient and scalable mission planning optimization method for a regular interplanetary transportation missions over a long time horizon. As more sustainable and long-term manned missions to Mars are being conceptualized, the need for a reliable and regular interplanetary cargo transportation system has also become increasingly prominent. However, planning the regular cargo transportation mission with the existing problem formulation had a limitation in computational scalability in the time dimension. The proposed method, or also termed as partially periodic time-expanded network, is constructed to compensate the past studies’ limitations and is shown to be computationally scalable and also capable of generating solutions that are practically preferred. A case study reveals the convergence of the initial mass low-Earth orbit (IMLEO) of the regular missions to the theoretical optimal solution as the number of cargo transportation missions increases.