Single-Machine Rescheduling of New Orders with Learning and Deterioration Effects Consideration

This paper explored single-machine rescheduling of new orders with both learning and deterioration effects consideration. According to the literature research, rescheduling means that a set of original jobs has already been scheduled to minimize classical objective, and later a new set of jobs arrives and creates a disruption. Two kinds of constraints, the maximum sequence disruption of the original jobs cannot exceed a fixed number and the maximum time disruption of the original jobs cannot exceed a known value, were examined. The objectives of this paper were to minimize total completion time based on the constraints respectively. We proved that both problems are solved in polynomial time algorithms.