# A generalized algorithm and framework for online 3-dimensional bin packing in an automated sorting center

arXiv: https://arxiv.org/abs/2111.01072 · HTML: https://mlsanity.com/paper/2111.01072/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Nov 2021.

## Built on by (most cited first, 1 of 1)

- [Effective Online 3D Bin Packing with Lookahead Parcels Using Monte Carlo Tree Search](https://mlsanity.com/paper/2601.02649/) (2026)

## Abstract (arXiv)

Online 3-dimensional bin packing problem (O3D-BPP) is getting renewed prominence due to the industrial automation brought by Industry 4.0. However, due to limited attention in the past and its challenging nature, a good approximate algorithm is in scarcity as compared to 1D or 2D problems. This paper considers real-time O3D-BPP of cuboidal boxes with partial information (look-ahead) in an automated robotic sorting center. We present two rolling-horizon mixed-integer linear programming (MILP) cum-heuristic based algorithms: MPack (for bench-marking) and MPackLite (for real-time deployment). Additionally, we present a framework OPack that adapts and improves the performance of BP heuristics by utilizing information in an online setting with a look-ahead. We then perform a comparative analysis of BP heuristics (with and without OPack), MPack, and MPackLite on synthetic and industry provided data with increasing look-ahead. MPackLite and the baseline heuristics perform within bounds of robot operations and thus, can be used in real-time.