A production situation is considered in which different items are produced on one machine. Setup times are incurred between the production of orders of different items. Production is driven by customer orders; each order concerns a batch of one product type and is furthermore completely characterized by its batchsize and (customer determined) due-date. Acceptance of orders may be refused if these orders are likely to cause late deliveries. The problem is to determine good acceptance strategies which naturally raises the question on what information such acceptance decisions have to be based. Three basic approaches are explored in this paper. In the monolithic approach, the acceptance decision is based on detailed information on a current production schedule for all formerly accepted orders. In the hierarchic approach, the acceptance strategy is based on global capacity load profiles only, while detailed scheduling of accepted orders takes place at a lower level (possibly later in time). In the myopic approach the acceptance decision is similar to the one in the hierarchic approach but scheduling is myopic, i.e. once the machine becomes idle only the next order to be produced is actually scheduled. The performances of these three approaches are compared by means of simulation experiments. The results indicate that the differences in performance are small. Insofar as the monolithic approach performs better, this is mainly due to the selective acceptance mechanism implicitely present in case of a heavy workload. An adaptation of the myopic approach to incorporate such a selective acceptance mechanism leads to a comparable performance