Scheduling identical parallel machines with tooling constraints

•We consider a job sequencing problem with tool requirements.•We solve the problem using adaptive large neighborhood search.•The algorithm is tested on instances with 200 jobs, 10 machines and 40 tools.•Computational results demonstrate the efficiency of the algorithm. We model and solve the problem of sequencing a set of jobs with specified processing times and tool requirements on a set of identical parallel machines. Decisions concern the assignment of jobs to machines, their sequencing, and the allocation of tools on each machine. The objective function minimizes the makespan. We propose two mathematical formulations of the problem and an adaptive large neighborhood search metaheuristic in which the destroy and repair operators exploit the structures of two well-known and related combinatorial optimization problems, namely the parallel machine scheduling problem and the job sequencing and tool switching problem on a single machine. Computational experiments conducted on two data sets of 1440 instances show that our algorithm produces excellent results and outperforms existing heuristics.