Virtual workflows and adaptive optimization scheduling of production process with feedback constraints

Feedback structure process often exists in production processes with precise quality requirements. The constraint of feedback process is conditional and reverse, and these peculiarities increase the complexity of scheduling problem. A dynamic scheduling model based on virtual workflows is designed and a scheduling optimization method with a new adaptive sequencing rule strategy is proposed for flexible production scheduling problem with feedback constraints. Based on feedback structure virtualization and virtual nodes responding to feedback disturbances, the dynamic scheduling model implements a mechanism for synchronizing the updating of task workflows and machine workflows with activities of feedback processes to trigger rescheduling. To adapt to the correlation between key dynamic features of scheduling scenario and multi-objective balance, the adaptive sequencing rule strategy with mean tardiness as dominant objective and makespan and energy consumption as regular objectives is proposed to improve multi-objective dynamic trade-off optimization performances of the scheduling method based on hybrid decision-making mechanism. Comparative tests are conducted to verify that the hybrid decision-making mechanism incorporating the proposed adaptive rule strategy can effectively improve the comprehensive dominance level of scheduling optimization results. Simulation tests show that the dynamic scheduling model can become a way to respond to feedback constraint disturbances and trigger rescheduling.

Authors

• Zhen Quan
• Yan Wang
• Xiang Liu Southeast University The Chinese University of Hong Kong
• Zhicheng Ji

Keywords

• Flexible production scheduling optimization
• Feedback constraint and disturbance
• Virtual workflow
• Hybrid decision-making mechanism
• Adaptive sequencing rule strategy