{"title":"Hot Rolling Scheduling of Heavy Plate Production Based on Heuristic and Ant Colony Algorithms","authors":"Jiangtao Xu, Jinliang Ding, Qing-da Chen, Ling Yi","doi":"10.1109/ICCSS53909.2021.9722019","DOIUrl":null,"url":null,"abstract":"Slab scheduling of hot rolling plays an important role in smart manufactory of heavy plate production. It faces the challenges of multiple specifications, small batch and characteristic mode of production. The wide-range fluctuation of product specifications leads the existing approaches difficult to used. To solve this problem, a novel slab scheduling approach based on heuristic and ant colony algorithms is proposed. The schedule problem is formulated in two stages, namely slab allocation and slab rolling sequence optimization. In the slab allocation stage, the strategy of selecting appropriate slabs from forward delivery is used. Then, an ant colony algorithm combined with a constraints handling strategy based on specification jump penalties is designed to solve the slab rolling sequence optimization problem. The computational experiments are carried out and the results demonstrate the effectiveness by the actual production data.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSS53909.2021.9722019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Slab scheduling of hot rolling plays an important role in smart manufactory of heavy plate production. It faces the challenges of multiple specifications, small batch and characteristic mode of production. The wide-range fluctuation of product specifications leads the existing approaches difficult to used. To solve this problem, a novel slab scheduling approach based on heuristic and ant colony algorithms is proposed. The schedule problem is formulated in two stages, namely slab allocation and slab rolling sequence optimization. In the slab allocation stage, the strategy of selecting appropriate slabs from forward delivery is used. Then, an ant colony algorithm combined with a constraints handling strategy based on specification jump penalties is designed to solve the slab rolling sequence optimization problem. The computational experiments are carried out and the results demonstrate the effectiveness by the actual production data.