An Intelligent Optimization Method of Reinforcing Bar Cutting for Construction Site
作者机构：Department of Civil Engineering and ArchitectureXi’an University of TechnologyXi’an710048China State Key Laboratory of Rail Transit Engineering Informatization(FSDI)Xi’an710043China Department of Computer Science and EngineeringXi’an University of TechnologyXi’an710048China
出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)
年 卷 期：2023年第134卷第1期
页 面：637-655页
核心收录：
学科分类：08[工学] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）]
基 金：funded by Nature Science Foundation of China(51878556) the Key Scientific Research Projects of Shaanxi Provincial Department of Education(20JY049) Key Research and Development Program of Shaanxi Province(2019TD-014) State Key Laboratory of Rail Transit Engineering Informatization(FSDI)(SKLKZ21-03)
主 题：Building construction rebar work cutting stock problem optimization algorithm integer linear programming
摘 要：To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable *** one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction *** cutting waste increases construction costs and generates a considerable amount of CO_(2)*** study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable *** the proposed algorithm,the integer linear programming algorithm was applied to solve the *** was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data *** proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction *** the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation *** the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.
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