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A General Heuristic Approach for Maximum Polygon Packing (CG Challenge)

Authors Canhui Luo , Zhouxing Su , Zhipeng Lü

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Author Details

Canhui Luo
  • Huazhong University of Science and Technology, Wuhan, China
Zhouxing Su
  • Huazhong University of Science and Technology, Wuhan, China
Zhipeng Lü
  • Huazhong University of Science and Technology, Wuhan, China

Funding

This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 72101094 and the Special Project for Knowledge Innovation of Hubei Province under Grant 2022013301015175.

Acknowledgements

We want to thank the organizers of CG:SHOP 2024 and all other participants for creating such an engaging challenge. We also want to thank Dominik Krupke for providing a helpful official validator for solutions.

Cite AsGet BibTex

Canhui Luo, Zhouxing Su, and Zhipeng Lü. A General Heuristic Approach for Maximum Polygon Packing (CG Challenge). In 40th International Symposium on Computational Geometry (SoCG 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 293, pp. 86:1-86:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.SoCG.2024.86

Abstract

This work proposes a general heuristic packing approach to address the Maximum Polygon Packing Problem introduced by the CG:SHOP 2024 Challenge. Our solver primarily consists of two steps: (1) Partitioning the container and polygons to form a series of small-scale subproblems; (2) For each subproblem, sequentially placing polygons into the container and attempting to eliminate overlaps.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Computing methodologies → Search methodologies
Keywords
  • packing
  • polygon
  • heuristic
  • differential evolution
  • local search
  • tabu search

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References

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