Minimizing mean flow times criteria on a single batch processing machine with non-identical job sizes

This paper considers the problem of scheduling jobs with non-identical capacity requirements or sizes on a single-batch processing machine to minimize the mean-flow times of jobs. A batch processing machine is one which can process up to B jobs simultaneously. The processing time of a batch is equal to the longest processing time among all jobs in the batch. We provide various new heuristics for this problem. Computational experiments show that the heuristics are capable of obtaining near-optimal solutions in very reasonable CPU times.