{"title":"钢铁厂中厚板设计问题的两阶段求解法","authors":"Gongzhuang Peng, Boyu Zhang, Shenglong Jiang","doi":"10.1049/cim2.12091","DOIUrl":null,"url":null,"abstract":"<p>The medium-thick plate is an important type of steel product widely used in construction and engineering machinery. The orders are usually characterised by multiple specifications and small quantities. The plate design is an important part in the production process of medium-thick plate, which includes the combination of sub-plates and the size design of the motherboard. A multi-objective model for medium-thick plate design is proposed based on the 2D bin packing model, comprehensively considering spatial and size constraints of the plate production. A two-stage genetic algorithm (TSGA) is developed to solve the proposed model. In the first stage, an improved GA is used to optimise the corresponding relationship between the sub-plates and the slab, as well as the size of the motherboard. In the second stage, an exact algorithm based on the integer programming model is applied to calculate the order layout to minimise the surplus materials. To validate the proposed method, computational experiments are conducted based on actual production data from a steel plant. The experimental results show the effectiveness of the TSGA algorithm in solving the plate design problem.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12091","citationCount":"0","resultStr":"{\"title\":\"A two-stage solution method for the design problem of medium-thick plates in steel plants\",\"authors\":\"Gongzhuang Peng, Boyu Zhang, Shenglong Jiang\",\"doi\":\"10.1049/cim2.12091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The medium-thick plate is an important type of steel product widely used in construction and engineering machinery. The orders are usually characterised by multiple specifications and small quantities. The plate design is an important part in the production process of medium-thick plate, which includes the combination of sub-plates and the size design of the motherboard. A multi-objective model for medium-thick plate design is proposed based on the 2D bin packing model, comprehensively considering spatial and size constraints of the plate production. A two-stage genetic algorithm (TSGA) is developed to solve the proposed model. In the first stage, an improved GA is used to optimise the corresponding relationship between the sub-plates and the slab, as well as the size of the motherboard. In the second stage, an exact algorithm based on the integer programming model is applied to calculate the order layout to minimise the surplus materials. To validate the proposed method, computational experiments are conducted based on actual production data from a steel plant. The experimental results show the effectiveness of the TSGA algorithm in solving the plate design problem.</p>\",\"PeriodicalId\":33286,\"journal\":{\"name\":\"IET Collaborative Intelligent Manufacturing\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12091\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Collaborative Intelligent Manufacturing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Collaborative Intelligent Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
A two-stage solution method for the design problem of medium-thick plates in steel plants
The medium-thick plate is an important type of steel product widely used in construction and engineering machinery. The orders are usually characterised by multiple specifications and small quantities. The plate design is an important part in the production process of medium-thick plate, which includes the combination of sub-plates and the size design of the motherboard. A multi-objective model for medium-thick plate design is proposed based on the 2D bin packing model, comprehensively considering spatial and size constraints of the plate production. A two-stage genetic algorithm (TSGA) is developed to solve the proposed model. In the first stage, an improved GA is used to optimise the corresponding relationship between the sub-plates and the slab, as well as the size of the motherboard. In the second stage, an exact algorithm based on the integer programming model is applied to calculate the order layout to minimise the surplus materials. To validate the proposed method, computational experiments are conducted based on actual production data from a steel plant. The experimental results show the effectiveness of the TSGA algorithm in solving the plate design problem.
期刊介绍:
IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly.
The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).