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DeepPack3D: A Python package for online 3D bin packing optimization by deep reinforcement learning and constructive heuristics

Yung Po Tsang, Daniel Y. Mo, K.T. Chung, C.K.M. Lee

发表年份
2024
引用次数
2

摘要

The rapid advancement of industrial robotic automation has increased the significance of online 3D bin packing optimization for applications, like palletization and container loading. Despite numerous learning-based methods emerging for informed decision-making in this process, the absence of a standardized benchmark makes it challenging to experience the process and validate new algorithms. To bridge this gap, we introduce DeepPack3D, a software package that integrates deep reinforcement learning and constructive heuristic approaches for online 3D bin packing optimization. DeepPack3D provides a foundation for benchmarking, allowing users to evaluate performance using customizable item lists and lookahead values, thereby facilitating consistent research advancements. • DeepPack3D is an open-source Python package for online 3D bin packing optimization. • Deep Q network and four different constructive heuristics are supported. • Lookahead value can be customized to support a flexible online optimization process.

关键词

Python (programming language)HeuristicsConstructiveBin packing problemBinComputer scienceReinforcement learningArtificial intelligenceTheoretical computer scienceProgramming language

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