Scheduling a dual-resource flexible job shop with makespan and due date-related criteria

Current struggles for customer satisfaction in make-to-order companies focus on product customization and on-time delivery. For better management of demand-mix variability, production activities are typically configured as flexible job shops. The advent of information technology and process automatization has given rise to very specific training requirement for workers, which indeed turns production scheduling into a dual-resource constrained problem. This paper states a novel dual-resource constrained flexible job-shop problem (DRCFJSP) whose performance considers simultaneously makespan and due date-oriented criteria, where eligibility and processing time are both dependent on worker expertise. Our research comes from an automobile collision repair shop with re-scheduling needs to react to real-time events like due date changes, delay in arrival, changes in job processing time and rush jobs. We have developed constructive iterated greedy procedures that performs efficiently on the large-scale bi-objective DRCFJSP arisen (good schedules in < 5 s), hence providing planners with the required responsiveness in their scheduling of repairing orders and allocation of workers at the different work centres. In addition, computational experiments were conducted on a test bed of smaller DRCFJSP instances generated for benchmarking purposes. Off-the-shelf resolution for an 80% of the medium-sized instances is not fruitful after 9000 s.