alexfrom0815/Online-3D-BPP-PCT
Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space. observed · 2026-08-28
Health v2 · maintenance only
61/100
- Activity 63
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1673
- days_rel: n/a
- days_push: 224
- n_releases_24m: 0
Adoption not part of the score
1045 stars · 58 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python research implementation of the ICLR 2022 paper 'Learning Efficient Online 3D Bin Packing on Packing Configuration Trees', using deep reinforcement learning over a hierarchical packing configuration tree. It supports arbitrary bin/item sizes, continuous solution spaces, packing stability approximation, and custom practical constraints.
Use cases
- solve online 3D bin packing with deep reinforcement learning
- pack boxes into a container with continuous item sizes
- approximate packing stability for 3D bin packing
- benchmark DRL packing against heuristic baselines
- handle custom constraints in 3D packing
- reproduce ICLR 2022 bin packing paper results
When to choose
- you need an online 3D bin packing solver with learned policies
- your items have continuous or arbitrary dimensions
- you need stability-aware or constraint-aware packing
- you want a research baseline for DRL-based packing
When to avoid
- you need offline (all-items-known) packing optimization
- you need irregular-shape or buffered packing (see the authors' IR-BPP repo)
- you want a production-ready commercial packing service
- you need a simple heuristic without ML dependencies
Facets
library · maturity active
machine-learning reinforcement-learning simulation artificial-intelligence reinforcement-learning logistics python cross-platform 3d-bin-packing deep-reinforcement-learning packing-configuration-tree online-packing iclr-2022 combinatorial-optimization research-code optimization algorithms linux
1 source
- readme: https://github.com/alexfrom0815/Online-3D-BPP-PCT · fetched 2026-08-28 · b4d3b484ba41
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| alexfrom0815/Online-3D-BPP-PCT | main | 61 |
For agents
markdown · JSON · MCP: product_card(name="alexfrom0815/Online-3D-BPP-PCT")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem