Order acceptance policy in Make-to-Order manufacturing based on average-reward reinforcement learning

Abstract

From the perspective of revenue management,a new approach for order acceptance under uncertainty in Make-to-Oder(MTO) manufacturing using average-reward reinforcement learning was proposed.In order to maximize the average expected revenue,the proposed approach took order types and different combinations of price and leadtime as criteria for the classification of the system states based on multi-level pricing mechanism.The simulation results show that the proposed algorithm has learning and selective ability to accept the order.Comparisons made with other order acceptance policies show the effectiveness of the proposed algorithm in average revenue,accepted order types,and adaptability.