Sequencing Orders from Multiple Industrial Customers on an External Manufacturing Facility

In this chapter, the system defined by a subcontractor, which processes orders generated from multiple customers, is cast into the dynamic single-machine sequencing framework. The subcontractor is modeled as a production/inventory facility that consists of a single, failure-free server and an input buffer with infinite capacity. Jobs arrive continuously to the system at random intervals and have stochastic processing times and due dates. A setup is required when switching from one job type to another. The behaviour of the system, when operating under various rescheduling policies and job dispatching schemes, is investigated using discrete-event simulation in a series of experiments. A reinforcement learning-based approach is proposed for dynamic dispatching rule selection under the completely reactive rescheduling policy. The reinforcement learning controller is applied to two simulation cases with the aim of generating state-dispatching rule mappings that minimize mean tardiness and mean lateness.