Mixed integer programming models for concurrent configuration design and scheduling in a reconfigurable manufacturing system

A reconfigurable manufacturing system can evolve its configuration to offer exactly the capacity and functionality needed for every demand period. For the reconfigurable manufacturing system with multi-part flow-line configuration simultaneously producing multiple parts within the same family, the production cost and the delivery time are closely related to its configuration and corresponding scheduling for certain demand period. Although studies on multi-part flow-line configuration design are abundant, studies on concurrent optimization of configuration design and scheduling for reconfigurable manufacturing system are scarce. First, a generic mixed integer nonlinear programming model for concurrent configuration design and scheduling is established to relax the limitation of the existing model, and then a mixed integer linear programming model is derived. The decisions of the two generalized models are to decide the amount of stations, the amount of identical machines and machines' configuration for every station, and assign parts to machines along the multi-part flow line together with sequencing assigned parts for each machine. Based on the mixed integer linear programming model, an exact epsilon-constraint method is developed to obtain the Pareto optimal solutions with tradeoffs between cost and tardiness. The validation of two models and the epsilon-constraint method is verified against two cases adapted from the literature.