|
|
Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2026 Vol.27 No.3 P.1-12
Hierarchical algorithm for large-scale irregular packing problems
Abstract: To address the challenge of large-scale packing problems, this paper proposes a novel hierarchical algorithm based on the geometrical classification of parts. The algorithm begins by classifying parts into three levels based on their area and fullness and then applies distinct packing strategies to each category. An innovative “shape matching” method is introduced, which, together with the “box stacking” (for rectangular parts) and “gravity packing,” forms a comprehensive hierarchical packing system. Level‑1 comprises large rectangular parts, which are arranged using the box stacking algorithm. By aligning the corner points of the parts’ bounding boxes, this method avoids the hooking issue commonly encountered in gravity packing. Level‑2 includes both large, irregular parts and medium-sized parts. They are first processed using the shape matching algorithm, where rotation and translation are applied to achieve contour complementarity. The quality of the match is evaluated using the shape matching coefficient (SMC). If the SMC fails to reach the preset quality threshold, the system switches to box stacking (for large, irregular parts) or gravity packing (for medium-sized parts). Level‑3 comprises the remaining smaller parts and those that failed to pack in the previous two levels. For these parts, shape matching is attempted first, and the system resorts to gravity packing in case of failure. The experimental and comparative results demonstrate that the proposed hierarchical algorithm achieves higher material utilization than the traditional gravity packing algorithm. This improvement is facilitated by the box stacking and shape matching strategies, which promote a more orderly and compact arrangement of parts.
Key words: Large-scale packing; Hierarchical algorithm; Box stacking; Shape matching; Gravity packing; Principle of minimum potential energy
华南理工大学土木与交通学院,中国广州市,510640
摘要:为解决大规模排样问题,本文提出一种基于零件几何分类的新型分级算法。该算法首先根据零件的面积和饱满度将其分为3个层级,然后对每个层级应用不同的排样策略。引入一种创新的"形状匹配"方法,该方法与"方盒堆砌"(针对矩形零件)和"重力排样"算法一起,形成一个综合的分级排样系统。第1级包含大型矩形零件,采用方盒堆砌算法进行排样。该方法通过对齐零件外接包围盒的角点,避免了重力排样中常见的勾挂问题。第2级包含大型不规则零件和中型零件。首先使用形状匹配算法处理这些零件--通过旋转和平移操作实现轮廓互补。通过形状匹配系数(SMC)评估匹配质量。如果SMC未达到预设的质量阈值,系统将切换至方盒堆砌(针对大型不规则零件)或重力排样(针对中型零件)。第3级包含剩余的小型零件和前面两级排样失败的零件。针对这些零件,系统优先尝试形状匹配算法,若匹配失败,则采用重力排样算法。实验和对比结果表明,与传统重力排样算法相比,分级排样算法实现了更高的材料利用率。这种改进得益于方盒堆砌和形状匹配算法,促进了零件更有序、紧密的排列。
关键词组:
References:
Open peer comments: Debate/Discuss/Question/Opinion
<1>
DOI:
10.1631/ENG.ITEE.2025.0080
CLC number:
TP301.6
Download Full Text:
Downloaded:
14
Download summary:
<Click Here>Downloaded:
10Clicked:
19
Cited:
0
On-line Access:
2026-03-23
Received:
2025-10-12
Revision Accepted:
2026-02-04
Crosschecked:
2026-03-23