Optimizing Two-Dimensional Irregular Pattern Packing with Advanced Overlap Optimization Techniques

Longhui Meng, Liang Ding, Aqib Mashood Khan (), Ray Tahir Mushtaq () and Mohammed Alkahtani
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Longhui Meng: School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China
Liang Ding: Nanjing WIT Science & Technology Co., Ltd., Nanjing 210012, China
Aqib Mashood Khan: College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Ray Tahir Mushtaq: Bio-Additive Manufacturing University-Enterprise Joint Research Center of Shaanxi Province, Department of Industrial Engineering, Northwestern Polytechnical University, Xi’an 710072, China
Mohammed Alkahtani: Department of Industrial Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia

Mathematics, 2024, vol. 12, issue 17, 1-19

Abstract: This research introduces the Iterative Overlap Optimization Placement (IOOP) method, a novel approach designed to enhance the efficiency of irregular pattern packing by dynamically optimizing overlap ratios and pattern placements. Utilizing a modified genetic algorithm, IOOP addresses the complexities of arranging irregular patterns in a given space, focusing on improving spatial and material efficiency. This study demonstrates the method’s superiority over the traditional Size-First Non-Iterative Overlap Optimization Placement technique through comparative analysis, highlighting significant improvements in spatial utilization, flexibility, and material conservation. The effectiveness of IOOP is further validated by its robustness in handling diverse pattern groups and its adaptability in adjusting pattern placements iteratively. This research not only showcases the potential of IOOP in manufacturing and design processes requiring precise spatial planning but also opens avenues for its application across various industries, underscoring the need for further exploration into advanced technological integrations for tackling complex spatial optimization challenges.

Keywords: irregular packing; modified genetic algorithm; overlap detection; spatial efficiency; iterative optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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