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Optimization Models for Reducing Off-Cuts of Raw Materials in Construction Site

Author

Listed:
  • Haoqing Wang

    (Faculty of Business, The Hong Kong Polytechnic University, Hong Kong, China)

  • Wen Yi

    (Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China)

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.

Suggested Citation

  • Haoqing Wang & Wen Yi, 2022. "Optimization Models for Reducing Off-Cuts of Raw Materials in Construction Site," Mathematics, MDPI, vol. 10(24), pages 1-16, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4651-:d:997643
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    References listed on IDEAS

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    1. Cui, Yaodong & Yang, Yuli, 2010. "A heuristic for the one-dimensional cutting stock problem with usable leftover," European Journal of Operational Research, Elsevier, vol. 204(2), pages 245-250, July.
    2. Cherri, Adriana Cristina & Arenales, Marcos Nereu & Yanasse, Horacio Hideki & Poldi, Kelly Cristina & Gonçalves Vianna, Andréa Carla, 2014. "The one-dimensional cutting stock problem with usable leftovers – A survey," European Journal of Operational Research, Elsevier, vol. 236(2), pages 395-402.
    3. Claudio Arbib & Fabrizio Marinelli & Fabrizio Rossi & Francesco Di Iorio, 2002. "Cutting and Reuse: An Application from Automobile Component Manufacturing," Operations Research, INFORMS, vol. 50(6), pages 923-934, December.
    4. Sotirios Dimitriadis & Evangelos Kehris, 2009. "Cutting stock process optimisation in custom door and window manufacturing industry," International Journal of Decision Sciences, Risk and Management, Inderscience Enterprises Ltd, vol. 1(1/2), pages 66-80.
    5. Luiz Maurício Maués & Norma Beltrão & Isabela Silva, 2021. "GHG Emissions Assessment of Civil Construction Waste Disposal and Transportation Process in the Eastern Amazon," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
    6. Delorme, Maxence & Iori, Manuel & Martello, Silvano, 2016. "Bin packing and cutting stock problems: Mathematical models and exact algorithms," European Journal of Operational Research, Elsevier, vol. 255(1), pages 1-20.
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