Predictive-reactive strategy for identical parallel machine rescheduling

Abstract Through new technologies development, customers can make or cancel an order at any time, which disrupts the established production schedule. This reality forced many companies to become sensitive in dealing with this situation through rescheduling processes. While efficiency criteria are used to assess the performance of a scheduling system, in dynamic environments, stability criteria measure the impact of job deviation. Differently from previous works, this paper investigates a new performance measure to simultaneously assess schedule efficiency by the total weighted waiting times, and schedule stability by the weighted completion time deviation. This mix could be a very helpful and significant criterion in industrial and health care environments. The studied problem considers an identical parallel machine rescheduling with jobs arriving over time. Based on a predictive-reactive strategy, a Mixed Integer Linear Programming model (MILP) is developed, as well as an iterative methodology for dealing with the online part. At last, numerical results are presented, discussing the impact of the efficiency-stability coefficient on the system performance, as well as the computing time to solve the described problem.