Innovative approaches to solar cell selection under complex intuitionistic fuzzy dynamic settings

Dilshad Alghazzawi; Maryam Liaqat; Hanan Alolaiyan; Hamiden Abd El-Wahed Khalifa; Alhanouf Alburaikan; Qin Xin; Umer Shuaib; Dilshad Alghazzawi; Maryam Liaqat; Hanan Alolaiyan; Hamiden Abd El-Wahed Khalifa; Alhanouf Alburaikan; Qin Xin; Umer Shuaib

doi:10.3934/math.2024409

AIMS Mathematics

2024, Volume 9, Issue 4: 8406-8438. doi: 10.3934/math.2024409

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Research article

Innovative approaches to solar cell selection under complex intuitionistic fuzzy dynamic settings

1.
Department of Mathematics, College of Science & Arts, King Abdul Aziz University, Rabigh, Saudi Arabia
2.
Department of Mathematics, Division of Science and Technology, University of Education, Lahore 54770, Pakistan
3.
Department of Mathematics, King Saud University, Riyadh, Saudi Arabia
4.
Department of Mathematics, College of Science, Qassim University, Buraydah, 51452, Saudi Arabia
5.
Department of Operations and Management Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
6.
Faculty of Science and Technology, University of the Faroe Islands, Vestara Bryggja 15, FO 100 Torshavn, Faroe Islands, Denmark
7.
Department of Mathematics, Government College University, Faisalabad 38000, Pakistan

Received: 08 December 2023 Revised: 23 January 2024 Accepted: 04 February 2024 Published: 28 February 2024
MSC : 90B50, 94D05

The need to meet current energy demands while protecting the interests of future generations has driven people to adopt regulatory frameworks that promote the careful use of limited resources. Among these resources, the sun is an everlasting source of energy. Solar energy stands out as a prime example of a renewable and environmentally friendly energy source. An imperative requirement exists for precise and dependable decision-making methods for the selection of the most efficacious solar cell. We aimed to address this particular issue. The theory of complex intuitionistic fuzzy sets (CIFS) adeptly tackles ambiguity, encompassing complex problem formulations characterized by both intuitionistic uncertainty and periodicity. We introduced two aggregation operators: The complex intuitionistic fuzzy dynamic ordered weighted averaging (CIFDOWA) operator and the complex intuitionistic fuzzy dynamic ordered weighted geometric (CIFDOWG) operator. Noteworthy features of these operators were stated, and significant special cases were meticulously outlined. An updated score function was devised to address the deficiencies, identified in the current score function within the context of CIF knowledge. In addition, we devised a methodical strategy for managing multiple attribute decision-making (MADM) problems that involve CIF data by implementing the proposed operators. To demonstrate the efficacy of the formulated algorithm, we presented a numerical example involving the selection of solar cells together with a comparative analysis with several well-established methodologies.
- CIFS,
- CIFDOWA operator,
- CIFDOWG operator,
- decision making,
- optimization,
- algorithms
Citation: Dilshad Alghazzawi, Maryam Liaqat, Hanan Alolaiyan, Hamiden Abd El-Wahed Khalifa, Alhanouf Alburaikan, Qin Xin, Umer Shuaib. Innovative approaches to solar cell selection under complex intuitionistic fuzzy dynamic settings[J]. AIMS Mathematics, 2024, 9(4): 8406-8438. doi: 10.3934/math.2024409

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Abstract

The need to meet current energy demands while protecting the interests of future generations has driven people to adopt regulatory frameworks that promote the careful use of limited resources. Among these resources, the sun is an everlasting source of energy. Solar energy stands out as a prime example of a renewable and environmentally friendly energy source. An imperative requirement exists for precise and dependable decision-making methods for the selection of the most efficacious solar cell. We aimed to address this particular issue. The theory of complex intuitionistic fuzzy sets (CIFS) adeptly tackles ambiguity, encompassing complex problem formulations characterized by both intuitionistic uncertainty and periodicity. We introduced two aggregation operators: The complex intuitionistic fuzzy dynamic ordered weighted averaging (CIFDOWA) operator and the complex intuitionistic fuzzy dynamic ordered weighted geometric (CIFDOWG) operator. Noteworthy features of these operators were stated, and significant special cases were meticulously outlined. An updated score function was devised to address the deficiencies, identified in the current score function within the context of CIF knowledge. In addition, we devised a methodical strategy for managing multiple attribute decision-making (MADM) problems that involve CIF data by implementing the proposed operators. To demonstrate the efficacy of the formulated algorithm, we presented a numerical example involving the selection of solar cells together with a comparative analysis with several well-established methodologies.

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