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Distributed feedback control algorithm in an auction-based manufacturing planning and control system

In today's manufacturing enterprise, customer service performance is highly dependent on the effectiveness of the company's manufacturing planning and control system (MPCS). Most of the current MPCSs that employ the centralised planning approach can have drawbacks, such as structural rigidity, difficulty in designing a control system, and lack of flexibility. An auction-based manufacturing planning and control system (AMPCS) allows negotiation-based decision making, however, the distributed scheduling algorithm usually attempts to achieve only its objective without considering the global objective, and a contradiction problem might occur between the local objective and the overall system performance. Therefore, the objective of this research is to develop a distributed scheduling algorithm called a closed-loop feedback simulation (CLFS) approach for an AMPCS which includes adaptive control of the auction-based bidding sequence to prevent the first bid first serve rule and may dynamically allocate production resources to operations. CLFS iteratively adjusts the bidding sequence using the deviation between the predicted completion time and the due date to improve the scheduling performance. The results obtained from the computational experiments show that the proposed CLFS algorithm can obviously improve production performance compared to previous studies.