Learning to solve single-batch-processing machine scheduling problem with two-dimensional packing constraints

doi:10.1016/j.cor.2026.107549

Learning to solve single-batch-processing machine scheduling problem with two-dimensional packing constraints

2026-05-21

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DOI：10.1016/j.cor.2026.107549

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Abstract

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• Two-stage deep reinforcement learning solution for 2D-SBPM. • Packing-Net demonstrates versatile applicability and high efficiency. • Sequence generator can directly generate solution to avoid invalid evaluations. • The learned strategies showcase high quality and remarkable adaptability.

Keywords:

Deep reinforcement learning

Single-batch-processing machine

Scheduling problem

Two-dimensional packing constraints

Sequence generation

Learning to solve single-batch-processing machine scheduling problem with two-dimensional packing constraints

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