SOURCE-LINKED INTELLIGENCE

Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

The one-dimensional bin packing problem (1D-BPP) is a classical NP-hard combinatorial optimization problem with applications ranging from logistics and manufacturing to cloud resource management. Although deep reinforcement learning (DRL) has become a competitive paradigm for data-driven optimization, most learned packing methods target 2D and 3D variants, and intelligent learned solvers for 1D-BPP remain scarce. In this paper, we present a novel end-to-end, size-agnostic graph reinforcement learning framework for 1D-BPP. We formulate the packing process as a Markov decision process on an item

Read original source ↗ Open in workspace

recordType

paper

region

Global