A Heuristic Packing Strategy for Eccentric-Shaped Parts

Efficient packing of irregular mechanical parts in limited container space is essential for reducing transportation and storage costs in automated manufacturing. This study focuses on eccentric-shaped parts characterized by geometric asymmetry, multiple orientations, and local irregularities, and proposes a two-stage three-dimensional packing strategy. In the first stage, an optimal single-layer layout is generated using a heuristic algorithm that combines grid scanning with a gravity-drop principle and tabu search to optimize part positions and orientations. In the second stage, the optimized layer template is vertically replicated with buffer layers to enhance stacking stability, ensuring feasible and non-overlapping arrangements. Comparative experiments with Best Fit, BLF, LHL, and Random methods show that the proposed approach increases average space utilization by 8.3%, 8.8%, 8.1%, and 15.5%, respectively, while maintaining high stability and reasonable computation time. The results demonstrate that this method achieves dense and stable packing, offering an effective solution for intelligent packing and automated production of irregular parts.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2025-12-23
DOI
https://doi.org/10.3390/app16010148
Primary Topic
Optimization and Packing Problems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Heuristic Packing Strategy for Eccentric-Shaped Parts

Jie Shan, Guangfei Jia, Zhizhong Wang
Applied Sciences
Optimization and Packing Problems
article

A Heuristic Packing Strategy for Eccentric-Shaped Parts

Jie Shan, Guangfei Jia, Zhizhong Wang
article en

Abstract

Efficient packing of irregular mechanical parts in limited container space is essential for reducing transportation and storage costs in automated manufacturing. This study focuses on eccentric-shaped parts characterized by geometric asymmetry, multiple orientations, and local irregularities, and proposes a two-stage three-dimensional packing strategy. In the first stage, an optimal single-layer layout is generated using a heuristic algorithm that combines grid scanning with a gravity-drop principle and tabu search to optimize part positions and orientations. In the second stage, the optimized layer template is vertically replicated with buffer layers to enhance stacking stability, ensuring feasible and non-overlapping arrangements. Comparative experiments with Best Fit, BLF, LHL, and Random methods show that the proposed approach increases average space utilization by 8.3%, 8.8%, 8.1%, and 15.5%, respectively, while maintaining high stability and reasonable computation time. The results demonstrate that this method achieves dense and stable packing, offering an effective solution for intelligent packing and automated production of irregular parts.

Applied SciencesVol. 16(1)
Hebei University of Science and Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Optimization and Packing Problems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.