mlsanityData to 14 Oct 2026

One4Many-StablePacker: An Efficient Deep Reinforcement Learning Framework for the 3D Bin Packing Problem

arXiv 2510.10057 ↗First posted 11 Oct 2025cs.LGcited by 0

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

The three-dimensional bin packing problem (3D-BPP) is widely applied in logistics and warehousing. Existing learning-based approaches often neglect practical stability-related constraints and exhibit limitations in generalizing across diverse bin dimensions. To address these limitations, we propose a novel deep reinforcement learning framework, One4Many-StablePacker (O4M-SP). The primary advantage of O4M-SP is its ability to handle various bin dimensions in a single training process while incorporating support and weight constraints common in practice. Our training method introduces two innovative mechanisms. First, it employs a weighted reward function that integrates loading rate and a new height difference metric for packing layouts, promoting improved bin utilization through flatter packing configurations. Second, it combines clipped policy gradient optimization with a tailored policy drifting method to mitigate policy entropy collapse, encouraging exploration at critical decision nodes during packing to avoid suboptimal solutions. Extensive experiments demonstrate that O4M-SP generalizes successfully across diverse bin dimensions and significantly outperforms baseline methods. Furthermore, O4M-SP exhibits strong practical applicability by effectively addressing packing scenarios with stability constraints.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 22 of its 52 references that are in the map. First posted on arXiv 11 Oct 2025.

Builds on

22 of 52 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024GOPT: Generalizable Online 3D Bin Packing via Transformer-based Deep Reinforcement Learning9 Sep
  2. 2024An Efficient Deep Reinforcement Learning Model for Online 3D Bin Packing Combining Object Rearrangement and Stable Placement19 Aug
  3. 2024Bin Packing Optimization via Deep Reinforcement Learning19 Mar

Other references · 19

  1. 2016Neural Combinatorial Optimization with Reinforcement Learningcited by 608
  2. 2017Learning Combinatorial Optimization Algorithms over Graphscited by 561
  3. 2025Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoningcited by 559
  4. 2025The Entropy Mechanism of Reinforcement Learning for Reasoning Language Modelscited by 485
  5. 2020Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instancescited by 162
  6. 2023Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalizationcited by 142
  7. 2020Online 3D Bin Packing with Constrained Deep Reinforcement Learningcited by 41
  8. 2017Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Methodcited by 31
  9. 2018Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimizationcited by 27
  10. 2024Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectivescited by 23
  11. 2021Learning Practically Feasible Policies for Online 3D Bin Packingcited by 18
  12. 2021Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attentioncited by 13
7 more
  1. 2022Learning Physically Realizable Skills for Online Packing of General 3D Shapescited by 12
  2. 2025CPGD: Toward Stable Rule-based Reinforcement Learning for Language Modelscited by 11
  3. 2020PackIt: A Virtual Environment for Geometric Planningcited by 10
  4. 2024SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branchcited by 9
  5. 2021One model Packs Thousands of Items with Recurrent Conditional Query Learningcited by 5
  6. 2023Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluationcited by 4
  7. 2025Deliberate Planning of 3D Bin Packing on Packing Configuration Treescited by 4

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  1. 2025A Hierarchical Bin Packing Framework with Dual Manipulators via Heuristic Search and Deep Reinforcement Learning
  2. 2026Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing
  3. 2026Effective Online 3D Bin Packing with Lookahead Parcels Using Monte Carlo Tree Search
  4. 2026Diffusion Reinforcement Learning Based Online 3D Bin Packing Spatial Strategy Optimization
  5. 2026Preference-Conditioned Reinforcement Learning for Space-Time Efficient Online 3D Bin Packing
  6. 2026Operationally Guided Placement-Aware Learning for Industrial Online 3D Bin Packing
  7. 2025HERB: Human-augmented Efficient Reinforcement learning for Bin-packing
  8. 2026PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing ↗