Robust Optimization Models of Integrated Configuration Design and Scheduling for Reconfigurable Flowline

Abstract

For the reconfigurable manufacturing system (RMS) with multi-part flow-line configuration producing multiples 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. Up to now, the study on robust optimization of configuration design and scheduling for RMS considering the uncertainty of operation processing time is absent. First, a scenario based robust optimization model for integrated configuration design and scheduling is established, which is a mixed integer nonlinear programming formulation. Then, a mixed integer linear programming (MILP) model is derived to minimize the sum of total cost, the cost variation for prescribed scenarios, and penalty of earliness and tardiness. Based on the MILP model, LINGO is used to obtain the optimal solution. The validation and advantages of the robust MILP model are illustrated against two cases adapted from the literature.