Three-Step Mathematical Model for Optimizing Rebar Cutting-Stock with Practical Application
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 7
Abstract
Theory of operations research is applied in this paper. The minimum total cost of steel reinforcement work was used as the objective function, and a three-step mathematical model to optimize the rebar cutting-stock was developed for building the finished rebars. Model I was applied to determine the whole raw material rebars that build the finished rebar. Models II and III were then applied to obtain the cut rebars needed to form the remaining rebar length of the finished rebar. The optimization results of the three-step model were combined to obtain a rebar cutting-stock list and method. Note the following results: (1) Considering comprehensively the effects of labor and material costs in the models led to the least rebar waste and number of welding spots, and thus the minimum total cost was reached. (2) In Model I, the minimum of cost sum of the rebar waste and welding spot count was taken as the objective to use the longer whole rebars first to minimize cutting and welding operations, and reducing the remaining rebar count reduced the subsequent calculation workload of Models II and III. (3) In model II, a constraint that every rebar section length be restricted to three nonoverlapping cases was imposed, which ensured that welding spots were not located in the midspan of a finished rebar. (4) In the practical case study considered, the rebar waste rate was 0.44%, and the finished rebars including 1 or 2 welding spots accounted for 90% of all finished rebars, which shows that the overall number of welding spots was small. The optimization not only clearly saved the rebar material cost but also decreased the labor cost of cutting and welding.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The authors gratefully acknowledge the financial supports by the National Natural Science Foundation of China (Grant No. 52074112), the Excellent Young and Middle-Aged Innovation Research Groups of Hubei Provincial Department of Education (T2021019), and Hubei Superior and Distinctive Discipline Group of New Energy Vehicle and Smart Transportation. Also, the authors would like to express their gratitude to EditSprings for the expert linguistic services provided.
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Published In
Journal of Construction Engineering and Management
Volume 148 • Issue 7 • July 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Sep 25, 2021
Accepted: Feb 3, 2022
Published online: Apr 19, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 19, 2022
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