Robust team assignment and scheduling for scalable digital art collaboration

Collaborative digital content creation in multi-stage artistic workflows requires effective coordination among heterogeneous creators and shared computational resources. However, many existing approaches overlook key constraints, such as cross-stage team continuity, task-specific temporal windows, and the compatibility between resources and assigned slots, which lead to resource contention and unstable collaboration structures. To address these limitations, this article proposes an optimization framework that integrates stage–slot scheduling with team formation to capture the structural complexity of digital art production. The framework incorporates temporal feasibility, slot capacity constraints, tool-stack compatibility, and inter-stage transition costs. We show that the objective function is monotone submodular, and develop a Greedy Team-Slot Assignment (GTSA) algorithm with a theoretical (1−1/e) approximation bound. The experiment results on synthetic data show that GTSA effectively reduces total cost and improves team stability compared with baseline heuristics, while achieving near-optimal performance relative to integer linear programming on small-scale instances and maintaining linear scalability as the problem size grows.