Control of manufacturing networks which contain a batch processing machine

We consider the control of a batch processing machine which is part of a larger manufacturing network of machines. Systems consisting of a batch processing machine and one or more unit-capacity machines in tandem are considered. The objective is to minimize the average time that jobs spend in the entire system. We present algorithms to determine the optimal policies for certain finite horizon, deterministic problems. We then discuss the structure of the optimal policies for infinite horizon, stochastic problems, and investigate the benefit of utilizing information about upstream and downstream unit-capacity machines in the control of the batch machine. We develop a simple heuristic scheduling policy to control the batch machine which takes into account the state of other machines in the network. Computational results demonstrate the effectiveness of our heuristic over a wide range of problem instances.