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Hyper heuristic method based on improved GEP for scheduling problems in shop floor

Considering the complex and inexplicit relationship between the working conditions and scheduling performance in shop floor, the paper proposed a hyper heuristic method based on gene expression programming (GEP) to customize efficient job dispatch rules and machine assignment rules for scheduling problems in shop floor. Since the traditional GEP has the shortcomings such as slow speed, inadequate precision and many parameters, which are not suitable for the actual environment, the paper made improvements on traditional GEP in two aspects: individual structure and the population evolution adaptation strategy. Through the simulation experiments the efficiency of the improved GEP machine learning approach is validated.