Irregular Packing Based on Principal Component Analysis Methodology

Irregular packing problems exist widely in industrial applications. To obtain better packing results, packing shapes are rotated freely during the packing process. However, equal angle-intervals are commonly used in the existing packing algorithms without considering the shape contour features, whic...

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Bibliographic Details
Published in:IEEE access 2018, Vol.6, p.62675-62686
Main Authors: Guo, Baosu, Liang, Zhuo, Peng, Qingjin, Li, Yongxin, Wu, Fenghe
Format: Article
Language:English
Subjects:
Algorithms
computer graphics
Dimensionality reduction
Feature extraction
forward line
Indexes
Industrial applications
irregular packing
Layout
Mathematical model
Optimization
optimization method
Principal component analysis
Principal components analysis
Rotation
Shape
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Summary:Irregular packing problems exist widely in industrial applications. To obtain better packing results, packing shapes are rotated freely during the packing process. However, equal angle-intervals are commonly used in the existing packing algorithms without considering the shape contour features, which may miss the best packing positions with the reduced packing quality. To solve this problem, an irregular packing algorithm is proposed based on a principal component analysis methodology in this paper. The principal components of convex features on the shapes are calculated. The rotation angles are then searched according to the first principal components. Finally, the shapes are rotated and packed based on the rotation angles. Experimental results show that the packing time is reduced and the material utilization is improved by the proposed algorithm.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2876546