Cooperative 3D printing (C3DP) is an emerging technology that employs multiple mobile 3D printers to work together on printing the desired part cooperatively for better scalability and more flexibility. In our previous work, we developed a chunker, a geometric partition tool, to divide a part into smaller chunks and a computational framework to automatically generate schedules for collision-free printing. However, the framework can only generate print schedules for one print job. To schedule multiple robots to print multiple jobs, job assignment and path planning for robots to move between jobs also needs to be considered. In this paper, we apply the previously developed framework to generate print schedules for multiple jobs concurrently, and then developed a new approach to combine the independent print schedules with two heuristic methods: 1) Job by Job heuristics and 2) Row by Row heuristics. Once a single schedule is generated using one of the two heuristics, the conflict-based search algorithm is used to find the optimal path for robots to move from one print location to next. A case study is conducted where three different jobs are concurrently scheduled on a floor with four available printing robots. The results validate the utility of the proposed approach in generating viable print schedules with collision-free path planning.