Predictive-reactive strategy for identical parallel machine rescheduling
Résumé
Through new technologies development, customers can create or cancel an order in real time, which disrupts the established production schedule. This realty forces many companies to quickly react for dealing with this situation through rescheduling processes. When efficiency usually measures the performance of a scheduling system, in dynamic environments, stability measures the impact of jobs deviation. Differently from previous works, this paper investigates a new approach to measure simultaneously efficiency by total weighted waiting times, and stability by weighted completion time deviation. This mix could be a very helpful and significant criterion in industrial and health care environments. This paper considers a parallel machine rescheduling problem with jobs arriving over time. Based on predictive-reactive strategy, a mixed integer linear programming model is developed, as well as an online iterative methodology to solve this rescheduling problem. Finally, numerical results are performed for studying the impact of efficiency and stability coefficient, as well as the computing time to solve the described problem.
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