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5G is expected to support ultra-reliable low latency communication to enable real-time applications such as industrial automation and control. 5G configured grant (CG) scheduling features a pre-allocated periodicity-based scheduling approach which reduces control signaling time and guarantees service quality. Although this enables 5G to support hard real-time periodic traffics, efficiently synthesizing the schedule and achieving high resource efficiency while serving multiple traffics, is still an open problem. To address this problem, we first formulate it using satisfiability modulo theories (SMT) so that an SMT-solver can be used to generate optimal solutions. For enhancing scalability, two efficient heuristic approaches are proposed. The experiments demonstrate the effectiveness and scalability of the proposed technique.