Advanced planning and scheduling with outsourcing in manufacturing supply chain

This paper considers advanced planning and scheduling (APS) in which each customer order has a due date and outsourcing is available. We present a model for APS that requires an absolute due date with outsourcing in a manufacturing supply chain. In practice, planning and scheduling are interrelated and should be solved simultaneously with outsourcing to ensure that the due dates of customer orders are met. The proposed model considers alternative process plans for job types, with precedence constraints for job operations. Such a model has not been treated in the literature. The integrated states include: (a) selecting the best machine for each operation, (b) deciding the sequence of operations, (c) picking the operations to be outsourced, and (d) minimizing the makespan for the due date of each order. To solve the model, a genetic algorithm (GA)-based heuristic approach was developed. In numerical experiments, the GA-based approach efficiently solved the APS model, and produced the best process plans (operation sequence and machine selection with outsourcing) and schedules for all orders.