A decision system with choice-based ranking and orthopair fuzzy data for prioritization of solar panels to facilitate solar energy


Krishankumar R., DİNÇER H., YÜKSEL S., Zavadskas E. K., Ravichandran K. S.

Annals of Operations Research, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Nəşrin Növü: Article / Article
  • Nəşr tarixi: 2025
  • Doi nömrəsi: 10.1007/s10479-025-06697-3
  • jurnalın adı: Annals of Operations Research
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Computer & Applied Sciences, INSPEC, Public Affairs Index, zbMATH, Civil Engineering Abstracts
  • Açar sözlər: Decision system, q-rung orthopair fuzzy set, Solar energy, Solar panels
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Yox

Qısa məlumat

Appropriate selection of solar panels is significant to facilitate solar power generation. With the help of this situation, it can be possible to minimize many problems, such as high maintenance and repair costs and lack of efficiency. However, there are very few studies in literature that determine the most importance of these factors. Accordingly, this study makes an evaluation related to the prioritization of solar panels to facilitate solar power generation. For this purpose, a new model has been established by combining different techniques. First, the weights of experts are determined through statistical variance method and selected criteria are weighted via q-ROF-CRITIC methodology. After that, solar panel types are ranked by using q-ROF-CRADIS method. The main contribution of this study is that a comprehensive analysis can be performed to generate an appropriate priority to select the viable solar panels with a novel framework. Regarding the methodological contribution, the use of CRADIS technique in the ranking of alternatives enhances the resemblance to human-driven decision making. Similarly, the biggest advantage of CRITIC is that the interactions among criteria are considered, and the proposed ranking algorithm enables choice-based ranking of solar panels that provides a sense of personalization during prioritization. The findings indicate that temperature coefficient is the most important factor to select the appropriate solar panel types. Similarly, availability also plays a key role in this context. On the other hand, polycrystalline silicon solar panel and thin film solar panel are found appropriate for the investment within the solar energy market.