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3D Bin Packing

As a classic NP-hard problem, the bin packing problem (1D-BPP) seeks for an assignment of a collection of items with various weights to bins. The optimal assignment houses all the items with the fewest bins such that the total weight of items in a bin is below the bin’s capacity. In its 3D version (3D-BPP), an item has a 3D “weight” corresponding to its length, width and height.

Papers

Showing 111 of 11 papers

TitleStatusHype
Learning Efficient Online 3D Bin Packing on Packing Configuration TreesCode2
Learning Practically Feasible Policies for Online 3D Bin PackingCode2
Online 3D Bin Packing with Constrained Deep Reinforcement LearningCode1
ASAP: Learning Generalizable Online Bin Packing via Adaptive Selection After Pruning0
Deliberate Planning of 3D Bin Packing on Packing Configuration Trees0
Online 3D Bin Packing Reinforcement Learning Solution with Buffer0
Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Method0
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing0
A Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packing0
A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem0
Three-Dimensional Bin Packing and Mixed-Case PalletizationCode0
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