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Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation

Author

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  • Qingpeng Cao

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

  • Moses Olabhele Esangbedo

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

  • Sijun Bai

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

  • Caroline Olufunke Esangbedo

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

Abstract

Selection of the most appropriate contractor for the installation of solar panels is essential to maximizing the benefit of this renewable, sustainable energy source. Solar energy is one of the 100% renewable energy sources, but implementation may not be very simple and cost-effective. A key phase in the implementation of renewable energy is the evaluation of contractors for the installation of solar panels, which is addressed as a multi-criteria decision-making (MCDM) problem. A new hybrid method is proposed that combines the stepwise weight analysis ratio assessment (SWARA) and full consistent method (FUCOM) weights that are represented as grey numbers used with traditional grey relational analysis (GRA) and evaluation based on distance from average solution (EDAS) methods. The ranking of contractors by both methods is the same, which confirmed the results presented in this research. The use of the grey SWARA-FUCOM weighting method combined with the GRA and EDAS methods increased the decision-makers’ (DMs) confidence in awarding the installation of the solar panel energy system to the top-ranked contractor.

Suggested Citation

  • Qingpeng Cao & Moses Olabhele Esangbedo & Sijun Bai & Caroline Olufunke Esangbedo, 2019. "Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation," Energies, MDPI, vol. 12(13), pages 1-30, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2481-:d:243597
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    3. Min-Yuan Cheng & Shu-Hua Yeh & Woei-Chyi Chang, 2020. "Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model," Sustainability, MDPI, vol. 12(11), pages 1-32, June.
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    5. Shrey Jain & Sunil Kumar Jauhar & Piyush, 2024. "A machine-learning-based framework for contractor selection and order allocation in public construction projects considering sustainability, risk, and safety," Annals of Operations Research, Springer, vol. 338(1), pages 225-267, July.
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