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Title: Optimization models for reducing off-cuts of raw materials in construction site
Authors: Wang, H 
Yi, W 
Issue Date: Dec-2022
Source: Mathematics, Dec. 2022, v. 10, no. 24, 4651
Abstract: More than ten billion tons of construction waste are generated every year in the world. The large volume of construction waste not only increases costs for contractors, but also poses a threat to the environment. A significant proportion of construction waste consists of off-cuts of raw materials. Therefore, to reduce construction waste, this study builds an optimization model to reduce the volume of off-cuts of raw materials. We then develop two solution methods—a mixed-integer linear programming method and a column generation method—to solve the proposed optimization model. We conduct numerical experiments to test the efficiency and applicability of our proposed model. The mixed-integer linear programming method obtains optimal solutions and is suitable for solving small-scale instances, whereas the column generation method gives high-quality solutions within seconds and is suitable for solving large-scale instances. In the large-scale instances, the column generation method reduces waste by over 10% compared to the use of two straightforward decisions rules. Our findings will help construction projects decrease material off-cuts, reduce costs, and achieve sustainable construction.
Keywords: Construction waste management
Green construction sites
Integer linear programming
Sustainable construction
Publisher: MDPI
Journal: Mathematics 
EISSN: 2227-7390
DOI: 10.3390/math10244651
Rights: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Wang H, Yi W. Optimization Models for Reducing Off-Cuts of Raw Materials in Construction Site. Mathematics. 2022; 10(24):4651 is available at https://doi.org/10.3390/math10244651.
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