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.

This article addresses the problem of subcontractor selection in an uncertain decision-making environment by proposing a new hybrid method and improving a classical multicriteria decision-making (MCDM) method. First, the proposed hybrid method combines subjective and objective weighting methods to estimate the weights of criteria that are represented as grey numbers. The subjective weighting method is the PA weighting method. The objective weighting method is the rank order centroid with slacks (ROCS) weighting method used to compensate for the limitation of the rank order centroid weighting method. Second, grey relational analysis (GRA) is improved by introducing both positive and negative reference (PNR) alternatives instead of a single reference alternative as in the classical GRA. Subsequently, the proposed hybrid grey-point allocation-ROCS weighting method and the GRA-PNR evaluation method are applied to select the most suitable subcontractor for the supply of heliostats for photothermal power station construction. Sensitivity analysis is conducted to verify the robustness of the results. Finally, the technique for order preferences by similarity to an ideal solution with grey values, simple additive weighting with grey relations, and additive ratio assessment with grey criteria scores is applied to validate the participation of the selected subcontractor in the project.