The use of multiple cooperating industrial robots provides efficient and flexible solutions to the manufacturing of complex aerospace structures. Such applications require the workloads to be sufficiently shared between neighboring robots, this entails the collision-free scheduling of many discrete tasks, where precedence orders need to be assigned for specific tasks. In this paper, we first present a two-step task allocation method that handles workload balancing, then a scheduling algorithm combining construction heuristic with iterated local search to provide efficient schedules. Our key innovation is a collision model that encodes precedence constraints and a fast heuristic that constructs collision-free schedule under given constraints, the optimization of the schedule is then addressed by an iterated local search. The advantage in terms of minimizing makespan under different problem scales and conditions is validated by computational experiments. Finally, the use of our method is demonstrated by a physical multi-robot system. • 2-step task allocation ensures workload balancing while dividing robot work regions. • Presenting a concise collision model based on implicitly partitioned working zone. • An MRS scheduling method combining insertion heuristic with iterated local search. • Robot operation safety is statistically analyzed and compared with the benchmarks. [ABSTRACT FROM AUTHOR]