Set with 72 instances for a complex parallel machine scheduling problem with batching considering family setup times, eligibility constraints, split jobs, machine capacity, release dates, and others. The instances have up to 10 machines and up to 100 operations to be scheduled. Operations are partitioned into families and grouped into jobs that depend on their execution to be completed. Each job has a weight (priority) that defines its importance. The problem is motivated by a real-life ship scheduling problem in the offshore oil and gas industry, with the machines representing the available fleet of vessels.