Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System
Optimal path planning algorithms offer substantial benefits in high-density storage (HDS) systems in modern smart manufacturing. However, traditional algorithms may encounter significant optimization challenges due to intricate architectural configurations and traffic constraints of the HDS system....
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/12/6764 |
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| author | Shuhan Zhang Yaqing Song Ziyu Chen Guo Chen Yongxin Cao Zhe Gao Xiaonong Xu |
| author_facet | Shuhan Zhang Yaqing Song Ziyu Chen Guo Chen Yongxin Cao Zhe Gao Xiaonong Xu |
| author_sort | Shuhan Zhang |
| collection | DOAJ |
| description | Optimal path planning algorithms offer substantial benefits in high-density storage (HDS) systems in modern smart manufacturing. However, traditional algorithms may encounter significant optimization challenges due to intricate architectural configurations and traffic constraints of the HDS system. This paper addresses these issues by introducing a two-step novel path planning method: (1) the mesh-tree grid map topological representation and the (2) Lattice-Hopping (LH) algorithm. The proposed method first converts the layout of an HDS system into a mesh-tree grid hierarchical structure by capturing and simplifying the spatial and geometrical information as well as the traffic constraints of the HDS system. Then, the LH algorithm is proposed to find optimal shipping path by leveraging the global connectivity of main tracks (main track priority) and the ‘jumping’ mechanism of sub-tracks. The main track priority and the ‘jumping’ mechanism work together to save computational complexity and enhance the feasibility and optimality of the proposed method. Numerical and case studies are performed to demonstrate the superiorities of our method to properly modified benchmark algorithms. Algorithm scalability, robustness, and operational feasibility for industrial production in modern smart manufacturing are also displayed and emphasized. |
| format | Article |
| id | doaj-art-f061f738c4df425c8c5c3edaeebe21c1 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-f061f738c4df425c8c5c3edaeebe21c12025-08-20T03:32:28ZengMDPI AGApplied Sciences2076-34172025-06-011512676410.3390/app15126764Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage SystemShuhan Zhang0Yaqing Song1Ziyu Chen2Guo Chen3Yongxin Cao4Zhe Gao5Xiaonong Xu6The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, ChinaThe College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, ChinaDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong 999077, ChinaNanjing Huade Storage Equipment Manufacturing Co., Ltd., Nanjing 211122, ChinaNanjing Huade Storage Equipment Manufacturing Co., Ltd., Nanjing 211122, ChinaThe College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, ChinaThe College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, ChinaOptimal path planning algorithms offer substantial benefits in high-density storage (HDS) systems in modern smart manufacturing. However, traditional algorithms may encounter significant optimization challenges due to intricate architectural configurations and traffic constraints of the HDS system. This paper addresses these issues by introducing a two-step novel path planning method: (1) the mesh-tree grid map topological representation and the (2) Lattice-Hopping (LH) algorithm. The proposed method first converts the layout of an HDS system into a mesh-tree grid hierarchical structure by capturing and simplifying the spatial and geometrical information as well as the traffic constraints of the HDS system. Then, the LH algorithm is proposed to find optimal shipping path by leveraging the global connectivity of main tracks (main track priority) and the ‘jumping’ mechanism of sub-tracks. The main track priority and the ‘jumping’ mechanism work together to save computational complexity and enhance the feasibility and optimality of the proposed method. Numerical and case studies are performed to demonstrate the superiorities of our method to properly modified benchmark algorithms. Algorithm scalability, robustness, and operational feasibility for industrial production in modern smart manufacturing are also displayed and emphasized.https://www.mdpi.com/2076-3417/15/12/6764high-density storage systemwarehousing logisticssmart manufacturinggrid-based path planning |
| spellingShingle | Shuhan Zhang Yaqing Song Ziyu Chen Guo Chen Yongxin Cao Zhe Gao Xiaonong Xu Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System Applied Sciences high-density storage system warehousing logistics smart manufacturing grid-based path planning |
| title | Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System |
| title_full | Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System |
| title_fullStr | Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System |
| title_full_unstemmed | Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System |
| title_short | Lattice-Hopping: A Novel Map-Representation-Based Path Planning Algorithm for a High-Density Storage System |
| title_sort | lattice hopping a novel map representation based path planning algorithm for a high density storage system |
| topic | high-density storage system warehousing logistics smart manufacturing grid-based path planning |
| url | https://www.mdpi.com/2076-3417/15/12/6764 |
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