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Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty

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  • Zahra Mohammadnazari

    (Iran University of Science and Technology)

  • Seyed Farid Ghannadpour

    (Iran University of Science and Technology)

Abstract

In this research, a supply chain network has been designed for inventory management using not only the project site storage facility but also an ancillary warehouse to keep materials. In order to make decision about the appropriate place for building the warehouse, multi-criteria decision-making techniques have been applied. Since the transportation sector, as the most important energy-consuming part, plays a significant role in global warming after power stations and the delivery of materials will have environmental impacts, this research tried to minimize the external cost of global warming caused by transportation. In this study, a mathematical formulation is presented to solve the problem of ordering the required amount to project site, while taking into account an ancillary warehouse. To quell the discussion, a numerical example has been demonstrated. The findings show that uncertainty considerations fortify the strict decision making and can increase the confidence level.

Suggested Citation

  • Zahra Mohammadnazari & Seyed Farid Ghannadpour, 2021. "Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10937-10972, July.
    • Handle: RePEc:spr:endesu:v:23:y:2021:i:7:d:10.1007_s10668-020-01095-0
    DOI: 10.1007/s10668-020-01095-0
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    References listed on IDEAS

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    1. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    2. Chandra Prakash Garg & Archana Sharma, 2020. "Sustainable outsourcing partner selection and evaluation using an integrated BWM–VIKOR framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 1529-1557, February.
    3. Yeo, Wee Meng & Yuan, Xue-Ming, 2011. "Optimal inventory policy with supply uncertainty and demand cancellation," European Journal of Operational Research, Elsevier, vol. 211(1), pages 26-34, May.
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    5. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    6. Jalili Marand, Ata & Li, Hongyan & Thorstenson, Anders, 2019. "Joint inventory control and pricing in a service-inventory system," International Journal of Production Economics, Elsevier, vol. 209(C), pages 78-91.
    7. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    8. Prak, Dennis & Teunter, Ruud, 2019. "A general method for addressing forecasting uncertainty in inventory models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 224-238.
    9. Rezaei, Jafar & van Roekel, Wilco S. & Tavasszy, Lori, 2018. "Measuring the relative importance of the logistics performance index indicators using Best Worst Method," Transport Policy, Elsevier, vol. 68(C), pages 158-169.
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    Cited by:

    1. Zahra Mohammadnazari & Amir Aghsami & Masoud Rabbani, 2023. "A hybrid novel approach for evaluation of resiliency and sustainability in construction environment using data envelopment analysis, principal component analysis, and mathematical formulation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(5), pages 4453-4490, May.
    2. Péter Dobos & Ákos Cservenák & Róbert Skapinyecz & Béla Illés & Péter Tamás, 2021. "Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems," Sustainability, MDPI, vol. 13(21), pages 1-33, October.
    3. Aspasia Koutsokosta & Stefanos Katsavounis, 2024. "Stochastic transitions of a mixed-integer linear programming model for the construction supply chain: chance-constrained programming and two-stage programming," Operational Research, Springer, vol. 24(3), pages 1-57, September.

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