Publications

Abstract : Multiple jobs are processed simultaneously on a given batch processing machine in parallel batching. The resulting batch is called a p-batch. Batching can lead to reduced production costs, but depending how the jobs are grouped into a batch can lead to better or worse delivery times of products. Scheduling jobs on batch processing machines requires grouping decisions in addition to the conventional assignment and sequencing decisions. Parallel batching is important in such diverse areas such as semiconductor manufacturing, aircraft manufacturing, shoe manufacturing, and healthcare. This paper surveys the literature on parallel batching and will focus primarily on deterministic scheduling. We provide a taxonomy of parallel batching problems, distinguishing the compatible case where all jobs can be used to form a batch from the incompatible families setting where only jobs from the same family can be used to form a batch. Makespan, flow time-, and due date-related measures are considered. We discuss scheduling approaches for single machines, parallel machines, and other environments such as flow shops and job shops. In addition to the discussion of archived and current papers, we discuss also recent trends in scheduling jobs on machines with parallel batch processing. Finally, we provide a discussion of future research directions for p-batch scheduling.