标杆管理
装箱问题
箱子
计算机科学
理论(学习稳定性)
软件
数据挖掘
多样性(控制论)
人工智能
算法
机器学习
营销
业务
程序设计语言
作者
Florian Kagerer,Maximilian Beinhofer,Stefan A. Stricker,Andreas Nüchter
标识
DOI:10.1177/02783649231193048
摘要
Many algorithms that were developed for solving three-dimensional bin packing problems use generic data for either experiments or evaluation. However, none of these datasets became accepted for benchmarking 3D bin packing algorithms throughout the community. To close this gap, this paper presents the benchmarking dataset for robotic bin packing problems (BED-BPP), which is based on realistic data. We show the variety of the dataset by elaborating an n-gram analysis. Besides, we propose an evaluation function, which contains a stability check that uses rigid body simulation. We demonstrated the application of our dataset on four different approaches, which we integrated in our software environment.
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