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

2021 Seventh Indian Control Conference (ICC) Pub Date : 2021-11-01 DOI:10.1109/ICC54714.2021.9703142

Ankush Ojha, Marichi Agarwal, Aniruddha Singhal, Chayan Sarkar, Supratim Ghosh, Rajesh Sinha

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引用次数: 2

Abstract

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.

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自动分拣中心三维在线装箱的广义算法与框架

由于工业4.0带来的工业自动化，在线三维装箱问题(O3D-BPP)再次受到重视。然而，由于过去的关注有限，以及它的挑战性，与一维或二维问题相比，一个好的近似算法是稀缺的。本文研究了机器人分拣中心中具有部分信息的立方体箱的实时O3D-BPP问题。我们提出了两种滚动水平混合整数线性规划(MILP)和启发式算法:MPack(用于基准测试)和MPackLite(用于实时部署)。此外，我们提出了一个框架OPack，该框架通过利用具有前瞻性的在线设置中的信息来适应和提高BP启发式的性能。然后，我们对BP启发式(带和不带OPack)、MPack和MPackLite在合成和工业提供的数据上进行了比较分析，并增加了前瞻性。MPackLite和基线启发式在机器人操作范围内执行，因此可以实时使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2021 Seventh Indian Control Conference (ICC)

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