Optimization for Storage Scheduling of Steel Plates Based on Cloud Manufacturing Platform
With the development of cloud manufacturing, the automation of storage scheduling becomes popular in the steel industry. However, the high customization of steel plates makes the storage scheduling too complex to be optimized. To overcome this challenge, we propose to utilize the big data of steel p...
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| Veröffentlicht in: | IEEE transactions on industrial informatics 2023-12, Vol.19 (12), p.1-10 |
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| creator | Wang, Jinlong Xu, Zhezhuang Wen, Weixiang Wang, Rong Lin, Ye Yuan, Yazhou Chen, Boyu Zhang, Qingdong |
| description | With the development of cloud manufacturing, the automation of storage scheduling becomes popular in the steel industry. However, the high customization of steel plates makes the storage scheduling too complex to be optimized. To overcome this challenge, we propose to utilize the big data of steel plate orders and warehouse status to optimize the storage scheduling of steel plates. The agglomerative hierarchical clustering is firstly adopted to reduce the complexity of excessive steel plate specifications, then an optimization problem is defined to formulate the storage scheduling of steel plates with safety. A two-stage heuristic (TSH) algorithm is proposed to solve the optimization problem with low complexity. In TSH, steel plates are firstly assigned to multiple stacks, and then the arrangement of each stack is determined. Experiments are executed based on a cloud manufacturing platform for steel plates production and storage, and the results prove the effectiveness of the proposed works. |
| doi_str_mv | 10.1109/TII.2023.3248109 |
| format | Article |
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However, the high customization of steel plates makes the storage scheduling too complex to be optimized. To overcome this challenge, we propose to utilize the big data of steel plate orders and warehouse status to optimize the storage scheduling of steel plates. The agglomerative hierarchical clustering is firstly adopted to reduce the complexity of excessive steel plate specifications, then an optimization problem is defined to formulate the storage scheduling of steel plates with safety. A two-stage heuristic (TSH) algorithm is proposed to solve the optimization problem with low complexity. In TSH, steel plates are firstly assigned to multiple stacks, and then the arrangement of each stack is determined. 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However, the high customization of steel plates makes the storage scheduling too complex to be optimized. To overcome this challenge, we propose to utilize the big data of steel plate orders and warehouse status to optimize the storage scheduling of steel plates. The agglomerative hierarchical clustering is firstly adopted to reduce the complexity of excessive steel plate specifications, then an optimization problem is defined to formulate the storage scheduling of steel plates with safety. A two-stage heuristic (TSH) algorithm is proposed to solve the optimization problem with low complexity. In TSH, steel plates are firstly assigned to multiple stacks, and then the arrangement of each stack is determined. Experiments are executed based on a cloud manufacturing platform for steel plates production and storage, and the results prove the effectiveness of the proposed works.</description><subject>agglomerative hierarchical clustering</subject><subject>Algorithms</subject><subject>cloud manufacturing</subject><subject>Cluster analysis</subject><subject>Clustering</subject><subject>Complexity</subject><subject>Complexity theory</subject><subject>Iron and steel industry</subject><subject>Job shop scheduling</subject><subject>Manufacturing</subject><subject>Optimization</subject><subject>Production</subject><subject>Scheduling</subject><subject>Slabs</subject><subject>Steel</subject><subject>steel plate</subject><subject>Steel plates</subject><subject>storage scheduling</subject><issn>1551-3203</issn><issn>1941-0050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkD1PwzAQhi0EEqWwMzBYYk45fySxR6j4qAQqUsvAZLnJuaRK42InA_x6XLUD051Oz_ue9BByzWDCGOi75Ww24cDFRHCp0uGEjJiWLAPI4TTtec4ywUGck4sYNwCiBKFH5HO-65tt82v7xnfU-UAXvQ92jXRRfWE9tE23pt6lK2JL31vbY6QPNmJNEz9t_VDTN9sNzlb9EPbwnkk920ty5mwb8eo4x-Tj6XE5fcle58-z6f1rVnHN-6xGlSuFlqtVUSLwomBlyfhK8pVTkoNSdamUzqtCSOlSRggNzJUaJGpXKTEmt4feXfDfA8bebPwQuvTScFVqoXiuZKLgQFXBxxjQmV1otjb8GAZmL9AkgWYv0BwFpsjNIdIg4j88CU3fxR9K4GsG</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Wang, Jinlong</creator><creator>Xu, Zhezhuang</creator><creator>Wen, Weixiang</creator><creator>Wang, Rong</creator><creator>Lin, Ye</creator><creator>Yuan, Yazhou</creator><creator>Chen, Boyu</creator><creator>Zhang, Qingdong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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However, the high customization of steel plates makes the storage scheduling too complex to be optimized. To overcome this challenge, we propose to utilize the big data of steel plate orders and warehouse status to optimize the storage scheduling of steel plates. The agglomerative hierarchical clustering is firstly adopted to reduce the complexity of excessive steel plate specifications, then an optimization problem is defined to formulate the storage scheduling of steel plates with safety. A two-stage heuristic (TSH) algorithm is proposed to solve the optimization problem with low complexity. In TSH, steel plates are firstly assigned to multiple stacks, and then the arrangement of each stack is determined. 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| subjects | agglomerative hierarchical clustering Algorithms cloud manufacturing Cluster analysis Clustering Complexity Complexity theory Iron and steel industry Job shop scheduling Manufacturing Optimization Production Scheduling Slabs Steel steel plate Steel plates storage scheduling |
| title | Optimization for Storage Scheduling of Steel Plates Based on Cloud Manufacturing Platform |
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