mlsanityData to 14 Oct 2026

Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluation

arXiv 2312.08103 ↗First posted 13 Dec 2023cs.LG cs.DScited by 4

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Abstract (arXiv)

The Bin Packing Problem (BPP) is a well-established combinatorial optimization (CO) problem. Since it has many applications in our daily life, e.g. logistics and resource allocation, people are seeking efficient bin packing algorithms. On the other hand, researchers have been making constant advances in machine learning (ML), which is famous for its efficiency. In this article, we first formulate BPP, introducing its variants and practical constraints. Then, a comprehensive survey on ML for multi-dimensional BPP is provided. We further collect some public benchmarks of 3D BPP, and evaluate some online methods on the Cutting Stock Dataset. Finally, we share our perspective on challenges and future directions in BPP. To the best of our knowledge, this is the first systematic review of ML-related methods for BPP.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 26 of its 81 references that are in the map. First posted on arXiv 13 Dec 2023.

Builds on

26 of 81 references.

References · 26

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14 more
  1. 2020Reinforcement Learning for Combinatorial Optimization: A Surveycited by 236
  2. 2017Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximationcited by 121
  3. 2020Online 3D Bin Packing with Constrained Deep Reinforcement Learningcited by 41
  4. 2017Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Methodcited by 31
  5. 2018Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimizationcited by 27
  6. 2018Stable bin packing of non-convex 3D objects with a robot manipulatorcited by 21
  7. 2021Learning Practically Feasible Policies for Online 3D Bin Packingcited by 18
  8. 2021Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attentioncited by 13
  9. 2019Reinforcement Learning Driven Heuristic Optimizationcited by 12
  10. 2020TAP-Net: Transport-and-Pack using Reinforcement Learningcited by 12
  11. 2020A Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packingcited by 11
  12. 2020PackIt: A Virtual Environment for Geometric Planningcited by 10
  13. 2022Online 3D Bin Packing Reinforcement Learning Solution with Buffercited by 8
  14. 2017Small Boxes Big Data: A Deep Learning Approach to Optimize Variable Sized Bin Packingcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Evaluating LLMs for Combinatorial Optimization: One-Phase and Two-Phase Heuristics for 2D Bin-Packingcited by 0
  2. 2025One4Many-StablePacker: An Efficient Deep Reinforcement Learning Framework for the 3D Bin Packing Problemcited by 0
  3. 2026Preference-Conditioned Reinforcement Learning for Space-Time Efficient Online 3D Bin Packingcited by 0
  4. 2026Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packingcited by 0