A batch process plant consists of individual plant items linked by a pipe network through which product is routed- During the operation of the plant, the availability of each item for configuration of process routes is severely constrained by the structure of the network, and the current arrangement of the valves which control the routeing. Current approaches to short term scheduling contain simplifying assumptions which ignore these constraints and this leads to unrealistic and infeasible schedules. This paper describes work done towards the development of a hybrid system, the batch process scheduler (BPS), which uses techniques from the areas of artificial intelligence (AI) and discrete event simulation (DES) in order to overcome these simplifying assumptions and develop good schedules which can be implemented in a plant.