The space mining mission is one of the major space business missions of the future. To earn a better profit and save the cost of space mining, missions must be optimized before the actual operation of the missions. Previous methods for space mission planning using a Generalized Multi-Commodity Network Flow (GMCNF) focused on scientific perspectives and neglected the profits. However, the objective of space business missions should be to maximize the benefit-cost ratio (BCR). With several linear constraints from the GMCNF and characteristics of space business missions, the problem could be expressed in Mixed Integer Linear Fractional Programming (MILFP) form. In this paper, we present a MILFP-GMCNF model based on a time-expanded network for space business mission planning. For a case study, a helium-3 mining mission is planned by computer simulation. By changing the variables of the simulation, the proposed method successfully optimized the missions in various situations. This method can be used in future space mining mission planning.
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