An effective predictive heuristic Model in single-machine systems under uncertainty

This paper takes a predictive scheduling approach to deal with machine disruption and uncertain job processing times in single-machine systems. A two-dimensional scale is proposed based on robustness and stability. The expected total realized tardiness of jobs and the expected sum of absolute deviation between the planned and realized job completion times are respectively considered as robustness and stability measures. Considering the total tardiness as a robustness measure includes due dates, the customer satisfaction enhancement level is achievable. We propose a novel heuristic to deal with such an NP-hard problem. Computational results show the proposed method's superiority in satisfying customers and staff and increasing systems accountability, especially in large-size problems over the common methods in the literature.