Batch scheduling for minimal energy consumption and tardiness under uncertainties: A heat treatment application

A novel multiple-objective model for batch scheduling of an energy-intensive manufacturing process, e.g., heat treatment, is proposed. The model minimizes energy consumption and total weighted tardiness while considering the arrival times of each workpiece and the inherent uncertainties in gas heating values, processing times, and due dates. Fuzzy logic is adopted to characterize these uncertainties and to interpret objective dominance when finding a Pareto frontier. A non-dominated sorting genetic algorithm is employed. The approach is demonstrated using a pre-treatment (soaking) process prior to a hot rolling operation. Pareto optimal performance of the model under different parameter settings is discussed.