https://scholar.dgist.ac.kr/handle/20.500.11750/58656 Wed, 08 Apr 2026 23:28:35 GMT 2026-04-08T23:28:35Z https://scholar.dgist.ac.kr/handle/20.500.11750/59931 Title: Evaluation of disposal techniques for electronic circuit board waste based on fuzzy multi-criteria decision analysis Author(s): Ijaz, Babu; Narayanamoorthy, Samayan; Sandra, Michael; Almakayeel, Naif; Dincer, Hasan; Yuksel, Serhat; Kang, Daekook Abstract: The rapid increase in electronic waste demands sustainable disposal solutions for non-recyclable circuit boards. This study introduces a novel fuzzy Multi-Criteria Decision Making (MCDM) framework that integrates Stepwise Weight Assessment Ratio Analysis (SWARA) for criteria weighting and the Ranking Alternatives by Perimeter Similarity (RAPS) method for evaluating disposal options under complex Pythagorean fuzzy environment. The proposed hybrid fuzzy model uniquely addresses linguistic ambiguity, expert hesitation, and conflicting criteria common in e-waste decision environments. Key criteria such as technological feasibility, environmental impact, cost, scalability, and energy use are assessed to identify the most suitable disposal strategy. Findings highlight environmental and technological factors as the most influential, with the top-ranked disposal method demonstrating strong suitability for end-of-life circuit boards. Sensitivity and comparative analyses validate the stability and reliability of the model. Overall, the study offers a practical and methodologically original decision-support tool for advancing sustainable electronic waste management. Sun, 30 Nov 2025 15:00:00 GMT https://scholar.dgist.ac.kr/handle/20.500.11750/59931 2025-11-30T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/59924 Title: An augmented fuzzy decision-making framework for evaluating renewable energy sources for hydrogen production: A case application to India Author(s): Brainy, Joseph Raj Vikilal Joice; Narayanamoorthy, Samayan; Sandra, Michael; Pamucar, Dragan; Nguyen, Phi-Hung; Pragathi, Subramaniam; Kang, Daekook Abstract: Hydrogen is the cleanest fuel, and its production from renewable sources is crucial for addressing energy and climate challenges. India’s renewable energy capacity presents an opportunity to produce environmentally friendly hydrogen for the international market. However, large-scale hydrogen production requires a thorough assessment of renewable energy sources under multiple constraints. This study introduces a fuzzy logic-based multistage assessment model to evaluate the feasibility of renewable energy-based hydrogen generation in India. A novel approach using bipolar complex linear diophantine fuzzy sets (BCLDFS) is proposed to account for both positive and negative perspectives in human judgment. The integration of bipolarity into the complex-valued structure of linear diophantine fuzzy sets enhances the precision of decision-making. Additionally, a modified BCLDF-level based weight assessment (LBWA)- multi-normalization multi-distance assessment (TRUST) method is developed as a multi-attribute decision-making (MADM) tool. This approach ranks renewable energy alternatives based on technical, economic, social, political, and environmental factors, along with 14 sub-criteria. This approach ranks renewable energy alternatives based on technical, economic, social, political, and environmental factors, along with 14 sub-criteria. In the case study focused on India, the proposed model identified solar energy as the most suitable renewable energy source for hydrogen production, followed by wind and hydro power. These results align with India’s green hydrogen priorities. A comparative and sensitivity analysis further validates the robustness of the proposed methodology, ensuring its reliability in strategic decision-making for sustainable hydrogen generation. Wed, 31 Dec 2025 15:00:00 GMT https://scholar.dgist.ac.kr/handle/20.500.11750/59924 2025-12-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/58954 Title: Fuzzy decision-analytics based lithium-ion battery selection for maximizing the efficiency of electric vehicles Author(s): Parthasarathy, Thirumalai Nallasivan; Narayanamoorthy, Samayan; Pamucar, Dragan Stevan S.; Kang, Daekook Abstract: The increasing reliance on fossil fuel-powered transportation significantly contributes to global warming and environmental change. Both industrial sectors and governmental bodies face challenges in addressing this issue through the adoption of green energy solutions. Electric vehicles present a more sustainable alternative due to their environmentally neutral characteristics and reduced operational costs. Batteries are integral to the functionality of electric vehicles, making the selection of an optimal battery essential. In this study, we conducted a comprehensive analysis to identify the most suitable lithium-ion batteries for the electric vehicle sector, employing fuzzy multi-criteria decision-making approaches (F-MCDM). We introduced a Complex Interval q-Rung Orthopair Fuzzy Set (CIVq-ROFS), which integrates three fuzzy sets: a complex fuzzy set, an interval-valued fuzzy set, and a q-rung orthopair fuzzy set. This integration yields more favorable outcomes compared to individual fuzzy sets. The proposed set is utilized for calculating attribute weights and ranking alternatives through the Criteria Importance Through Intercriteria Correlation (CRITIC) and Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) method. The algorithm was tested in a case study with five alternatives and six attributes, indicating a preference for the lithium nickel cobalt aluminum oxide battery for electric vehicles. The validity of the proposed model was established by comparing it with eight F-MCDM approaches, along with Spearman rank correlation and four sensitivity analyses to evaluate their effectiveness and robustness. Fri, 31 Oct 2025 15:00:00 GMT https://scholar.dgist.ac.kr/handle/20.500.11750/58954 2025-10-31T15:00:00Z