IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v23y2021i7d10.1007_s10668-020-01095-0.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-020-01095-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-020-01095-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Zheng, Xiaojin & Yin, Meixia & Zhang, Yanxia, 2019. "Integrated optimization of location, inventory and routing in supply chain network design," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 1-20.
    7. 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.
    8. 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.
    9. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ertunç, Ela & Uyan, Mevlut, 2022. "Land valuation with Best Worst Method in land consolidation projects," Land Use Policy, Elsevier, vol. 122(C).
    2. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    3. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    4. van de Kaa, Geerten & Janssen, Marijn & Rezaei, Jafar, 2018. "Standards battles for business-to-government data exchange: Identifying success factors for standard dominance using the Best Worst Method," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 182-189.
    5. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    6. Tavana, Madjid & Khalili Nasr, Arash & Mina, Hassan & Michnik, Jerzy, 2022. "A private sustainable partner selection model for green public-private partnerships and regional economic development," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    7. Fahim, Patrick B.M. & Rezaei, Jafar & Montreuil, Benoit & Tavasszy, Lorant, 2022. "Port performance evaluation and selection in the Physical Internet," Transport Policy, Elsevier, vol. 124(C), pages 83-94.
    8. Torkayesh, Ali Ebadi & Pamucar, Dragan & Ecer, Fatih & Chatterjee, Prasenjit, 2021. "An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    9. Amin Vafadarnikjoo & Madjid Tavana & Tiago Botelho & Konstantinos Chalvatzis, 2020. "A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria," Annals of Operations Research, Springer, vol. 289(2), pages 391-418, June.
    10. Haoran Zhao & Huiru Zhao & Sen Guo, 2018. "Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model," Sustainability, MDPI, vol. 10(7), pages 1-23, June.
    11. Shih-Chia Chang & Ming-Tsang Lu & Mei-Jen Chen & Li-Hua Huang, 2021. "Evaluating the Application of CSR in the High-Tech Industry during the COVID-19 Pandemic," Mathematics, MDPI, vol. 9(15), pages 1-16, July.
    12. Mahlet Demere Tadesse & Helen Zewdie Kine & Girma Gebresenbet & Lóránt Tavasszy & David Ljungberg, 2022. "Key Logistics Performance Indicators in Low-Income Countries: The Case of the Import–Export Chain in Ethiopia," Sustainability, MDPI, vol. 14(19), pages 1-25, September.
    13. Roya Ghamari & Mohammad Mahdavi-Mazdeh & Seyed Farid Ghannadpour, 2022. "Resilient and sustainable supplier selection via a new framework: a case study from the steel industry," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 10403-10441, August.
    14. Dilupa Nakandala & Yung Po Tsang & Henry Lau & Carman Ka Man Lee, 2022. "An Industrial Blockchain-Based Multi-Criteria Decision Framework for Global Freight Management in Agricultural Supply Chains," Mathematics, MDPI, vol. 10(19), pages 1-23, September.
    15. S. S. Ganji & A. N. Ahangar & Samaneh Jamshidi Bandari, 2022. "Evaluation of vehicular emissions reduction strategies using a novel hybrid method integrating BWM, Q methodology and ER approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(10), pages 11576-11614, October.
    16. Munim, Ziaul Haque & Duru, Okan & Ng, Adolf K.Y., 2022. "Transhipment port's competitiveness forecasting using analytic network process modelling," Transport Policy, Elsevier, vol. 124(C), pages 70-82.
    17. Chong Li & He Huang & Ya Luo, 2022. "An Integrated Two-Dimension Linguistic Intuitionistic Fuzzy Decision-Making Approach for Unmanned Aerial Vehicle Supplier Selection," Sustainability, MDPI, vol. 14(18), pages 1-24, September.
    18. Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    19. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory," Energies, MDPI, vol. 11(7), pages 1-24, July.
    20. Hamid Reza Fazeli & Qingjin Peng, 2023. "Integrated approaches of BWM-QFD and FUCOM-QFD for improving weighting solution of design matrix," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1003-1020, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:endesu:v:23:y:2021:i:7:d:10.1007_s10668-020-01095-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.