Papers 3D Bin Packing
“3D Bin Packing” 태그가 달린 논문 11편 · 필터 해제
Deliberate Planning of 3D Bin Packing on Packing Configuration Trees
Online 3D Bin Packing Problem (3D-BPP) has widespread applications in industrial automation. Existing methods usually solve the problem with limited resolution of spatial discretization, and/or cannot deal with complex p…
3D Bin PackingDeep Reinforcement LearningASAP: Learning Generalizable Online Bin Packing via Adaptive Selection After Pruning
Recently, deep reinforcement learning (DRL) has achieved promising results in solving online 3D Bin Packing Problems (3D-BPP). However, these DRL-based policies may perform poorly on new instances due to distribution shi…
3D Bin PackingDecision MakingDeep Reinforcement LearningMeta-LearningAdjustable Robust Reinforcement Learning for Online 3D Bin Packing
Designing effective policies for the online 3D bin packing problem (3D-BPP) has been a long-standing challenge, primarily due to the unpredictable nature of incoming box sequences and stringent physical constraints. Whil…
3D Bin PackingDeep Reinforcement Learningreinforcement-learningReinforcement LearningOnline 3D Bin Packing Reinforcement Learning Solution with Buffer
The 3D Bin Packing Problem (3D-BPP) is one of the most demanded yet challenging problems in industry, where an agent must pack variable size items delivered in sequence into a finite bin with the aim to maximize the spac…
3D Bin PackingData AugmentationGPUreinforcement-learning+2Learning Efficient Online 3D Bin Packing on Packing Configuration Trees
Online 3D Bin Packing Problem (3D-BPP) has widespread applications in industrial automation and has aroused enthusiastic research interest recently. Existing methods usually solve the problem with limited resolution of s…
3D Bin PackingDeep Reinforcement LearningLearning Practically Feasible Policies for Online 3D Bin Packing
We tackle the Online 3D Bin Packing Problem, a challenging yet practically useful variant of the classical Bin Packing Problem. In this problem, the items are delivered to the agent without informing the full sequence in…
3D Bin PackingCollision AvoidanceDeep Reinforcement LearningA Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packing
We propose a Deep Reinforcement Learning (Deep RL) algorithm for solving the online 3D bin packing problem for an arbitrary number of bins and any bin size. The focus is on producing decisions that can be physically impl…
3D Bin PackingDeep Reinforcement Learningreinforcement-learningReinforcement Learning+1Online 3D Bin Packing with Constrained Deep Reinforcement Learning
We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP). In our problem, the agent has limited information about the items to be packed into the bin, and an item must be packed immediatel…
3D Bin PackingCollision AvoidanceDeep Reinforcement Learningreinforcement-learning+2Three-Dimensional Bin Packing and Mixed-Case Palletization
Despite its wide range of applications, the three-dimensional bin-packing problem is still one of the most difficult optimization problems to solve. Currently, medium- to large-size instances are only solved heuristicall…
3D Bin PackingA Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem
A 3D flexible bin packing problem (3D-FBPP) arises from the process of warehouse packing in e-commerce. An online customer's order usually contains several items and needs to be packed as a whole before shipping. In part…
3D Bin PackingCombinatorial OptimizationSolving a New 3D Bin Packing Problem with Deep Reinforcement Learning Method
In this paper, a new type of 3D bin packing problem (BPP) is proposed, in which a number of cuboid-shaped items must be put into a bin one by one orthogonally. The objective is to find a way to place these items that can…
3D Bin PackingCombinatorial OptimizationDeep Reinforcement Learningreinforcement-learning+2