Robust Dynamic Scheduling with Uncertain Release Time for the Steelmaking-Continuous Casting Production

Abstract

The dynamic scheduling problem with uncertain release time in the steelmaking-continuous casting (SCC) production process is studied in this paper. Different from the existing dynamic scheduling strategies, a novel robust dynamic scheduling approach (RDSA) based on release time series forecasting is proposed in this paper. The proposed RDSA consists of two parts, offline preparation and online robust dynamic scheduling. In the offline preparation part, a release time series forecasting model is built by using the historical data, and the forecasting accuracy of the model is calculated. In the online robust dynamic scheduling part, a chance constrained programming (CCP) model is built first for rescheduling based on the predicted release time series and the statistical information of forecasting accuracy. Then, a robust schedule is generated by using the Monte Carlo simulation and evolutionary algorithm to solve the CCP model. Computational experiments based on the real data of a steel plant in China show that the proposed RDSA has a better performance than the classical approach in obtaining a robust schedule in the dynamic environment with uncertain release time.