Abstract
This study proposes a novel multiple-criteria group decision-making (MCGDM) approach for addressing marine debris caused by the excessive use of synthetic materials. The method integrates the intuitionistic double hierarchy linguistic term set (IDHLTS) with the TODIM framework to enhance decision-making under uncertainty. The IDHLTS combines the features of double hierarchy linguistic term sets with intuitionistic fuzzy sets, thereby capturing both membership and non-membership information to represent expert judgments more accurately. To aggregate decision information effectively, Hamacher operational rules and aggregation operators are employed due to their flexible, parametric nature. Furthermore, transformation functions, score functions, and distance measures are formally defined, and their mathematical properties are analyzed to ensure reliability. The TODIM method is incorporated to account for decision makers’ behavioral preferences, particularly loss aversion. To illustrate its practical relevance, a real-world case study is conducted to identify the most effective algal species for the remediation of synthetic debris in marine ecosystems. Microalgae are emphasized for their ability to decompose polymers through enzymatic and bioactive secretions, converting them into smaller fragments and assimilating the released carbon as a nutrient source. By applying the proposed MCGDM framework, environmentally sustainable algae with minimal ecological disruption are identified. Comparative analysis using classical approaches to MCDM, such as TOPSIS, weighted sum model (WSM), three-way decision (TWD), and grey relational analysis (GRA), it appears that despite slight variations in the intermediate ranking, all approaches find the same best and worst alternatives. It is notable that the proposed IDHLTS-TODIM approach encompasses more discrimination between alternatives by using the group decision-making structure, and the loss aversion behavior, which are not sufficiently considered by the benchmark approaches. The sensitivity analysis at various settings of the parameters also supports the stability and soundness of the ranking results. Sensitivity analysis further validates the feasibility, robustness, and stability of the proposed method. The findings demonstrate practical value of the approach, providing policymakers, environmental researchers, and marine conservationists with a systematic decision-support tool for implementing algae-based bioremediation strategies to mitigate synthetic marine debris.
Data availability
The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.
References
Arora, Y., Sharma, S. & Sharma, V. Microalgae in bioplastic production: a comprehensive review. Arab. J. Sci. Eng. 48(6), 7225–7241 (2023).
Ethiraj, S. & Samuel, M. S. A comprehensive review of the challenges and opportunities in microalgae-based wastewater treatment for eliminating organic, inorganic, and emerging pollutants. Biocatal. Agric. Biotechnol. 60, 103316 (2024).
Ghernaout, B., Ghernaout, D. & Saiba, A. Algae and cyanotoxins removal by coagulation/flocculation: A review. Desalin. Water Treat. 20(1–3), 133–143 (2010).
Zhang, X., Yang, Z., Wang, Y., Gao, B. Y. & Yue, Q. The removal efficiency and reaction mechanism of aluminum coagulant on organic functional groups-carboxyl and hydroxyl. Chem. Eng. J. 211, 186–194 (2012).
Iwuozor, K. O. Prospects and challenges of using coagulation-flocculation method in the treatment of effluents. Adv. J. Chem. Sect. A 2(2), 105–127 (2019).
Sabiri, N. E., Castaing, J. B., Massé, A. & Jaouen, P. Performance of a sand filter in removal of micro-algae from seawater in aquaculture production systems. Environ. Technol. 33(6), 667–676 (2012).
Simpson, D. R. Biofilm processes in biologically active carbon water purification. Water Res. 42(12), 2839–2848 (2008).
Su, L. et al. Creep characterisation and microstructural analysis of municipal solid waste incineration fly ash geopolymer backfill. Sci. Rep. 14(1), 29828. https://doi.org/10.1038/s41598-024-81426-7 (2024).
Jiang, W., Yang, L. & Bu, Y. Research on the Identification and Classification of Marine Debris Based on Improved YOLOv8. J. Mar. Sci. Eng. 12(10), 1748. https://doi.org/10.3390/jmse12101748 (2024).
Peng, S. et al. Enhanced assessment of chlorophyll-a and total nitrogen dynamics using unmanned aerial vehicle-based model and hyperspectral imagery in coastal wetland water. Environ. Technol. Innov. 40, 104521. https://doi.org/10.1016/j.eti.2025.104521 (2025).
Li, Z., Li, G., Song, X. & Wang, X. An Efficient and Dynamic Framework for Multi-Scale Target Detection of Underwater Organisms. J. Ocean Univ. China https://doi.org/10.1007/s11802-026-6062-9 (2025).
Huang, K. et al. Deciphering the ammonia transformation mechanism of a novel marine multi-stress-tolerant yeast, Pichia kudriavzevii HJ2, as revealed by integrated omics analysis. Appl. Environ. Microbiol. 91(6), e0221124. https://doi.org/10.1128/aem.02211-24 (2025).
Zadeh, L. A., Klir, G. J., & Yuan, B. Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers (Vol. 6). World scientific. (1996)
Atanassov, K. T. Intuitionistic fuzzy sets. In Intuitionistic fuzzy sets: theory and applications 1–137 (Physica-Verlag HD, Heidelberg, 1999).
Kaur, P., & Priya, A. Selection of inventory policy under Pythagorean fuzzy environment. Science & Technology Asia, pp. 62–71 (2020).
Kaur, S. & Gupta, S. K. A fuzzy-based framework for evaluation of website design quality index. Int. J. Digit. Libr. 22(1), 15–47 (2021).
Zadeh, L.A. Fuzzy languages and their relation to human and machine intelligence. In Fuzzy Sets, Fuzzy Logic, And Fuzzy Systems: Selected Papers by Lotfi A Zadeh (pp. 148–179) (1996).
Liu, D., Cheng, Y. & Peng, D. The multiple interacting fuzzy linguistic set and its application in emergency decision making. Expert Syst. Appl. 245, 123100 (2024).
Morente-Molinera, J. A., Wu, X., Morfeq, A., Al-Hmouz, R. & Herrera-Viedma, E. A novel multi-criteria group decision-making method for heterogeneous and dynamic contexts using multi-granular fuzzy linguistic modelling and consensus measures. Inf. Fusion 53, 240–250 (2020).
Gou, X., Liao, H., Xu, Z. & Herrera, F. Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures. Inf. Fusion 38, 22–34 (2017).
Li, X., Xu, Z. & Wang, H. Three-way decisions based on some Hamacher aggregation operators under double hierarchy linguistic environment. Int. J. Intell. Syst. 36(12), 7731–7753 (2021).
Fu, Z. & Liao, H. Unbalanced double hierarchy linguistic term set: The TOPSIS method for multi-expert qualitative decision making involving green mine selection. Inf. Fusion 51, 271–286 (2019).
Krishankumar, R., Pamucar, D., Deveci, M. & Ravichandran, K. S. Prioritization of zero-carbon measures for sustainable urban mobility using integrated double hierarchy decision framework and EDAS approach. Sci. Total Environ. 797, 149068 (2021).
Hamacher, H. Über logische Verknüpfungen unscharfer Aussagen und daren zugeharige Bewertungs-functionene, Progress in Cybernetics and Systems Research Vol. m. ed. by Trappl, R. and Klir, GJ and Riccardi, L, John Wiley and Sons, New York, 276, 288 (1979).
Wang, W. & Liu, X. Intuitionistic fuzzy information aggregation using Einstein operations. IEEE Trans. Fuzzy Syst. 20(5), 923–938 (2012).
Wang, W. & Liu, X. Intuitionistic fuzzy geometric aggregation operators based on Einstein operations. Int. J. Intell. Syst. 26(11), 1049–1075 (2011).
Wu, Q., Wu, P., Zhou, L., Chen, H., & Guan, X. Some new Hamacher aggregation operators under single-valued neutrosophic 2-tuple linguistic environment and their applications to multi-attribute group decision making. Comput. Ind. Eng. 116, 144–162 (2018).
Kaur, P., Dutta, V., Pradhan, B. L., Haldar, S. & Chauhan, S. A Pythagorean fuzzy approach for sustainable supplier selection using TODIM. Math. Probl. Eng. 2021, 4254894. https://doi.org/10.1155/2021/4254894 (2021).
Lourenzutti, R. & Krohling, R. A. TODIM based method to process heterogeneous information. Proc. Comput. Sci. 55, 318–327 (2015).
Savari, M. & Khaleghi, B. Analysis of psychological and social factors affecting climate change adaptation and mitigation behaviors among Iranian rice farmers. Sci. Rep. 15, 30431. https://doi.org/10.1038/s41598-025-30431 (2025).
Savari, M., Ghezi, M. & Molavi, H. Encouraging low-water-use crops: Behavioral drivers and policy recommendations for sustainable water management. Environ. Sustain. Indic. https://doi.org/10.1016/j.indic.2025.100711 (2025).
Tosun, Ö. & Akyüz, G. A fuzzy TODIM approach for the supplier selection problem. Int. J. Comput. Intell. Syst. 8(2), 317–329 (2015).
Liu, P. & You, X. Probabilistic linguistic TODIM approach for multiple attribute decision-making. Granul. Comput. 2, 333–342 (2017).
Wu, Q., Liu, X., Qin, J., Wang, W. & Zhou, L. A linguistic distribution behavioral multi-criteria group decision making model integrating extended generalized TODIM and quantum decision theory. Appl. Soft Comput. 98, 106757 (2021).
Wang, X., Gou, X., & Xu, Z. A continuous interval-valued double hierarchy linguistic GLDS method and its application in performance evaluation of bus companies. Appl. Intell. 1-16 (2022).
Dutta, V., Haldar, S., Kaur, P. & Gajpal, Y. Comparative analysis of TOPSIS and TODIM for the performance evaluation of foreign players in Indian Premier League. Complexity 2022(1), 9986137. https://doi.org/10.1155/2022/9986137 (2022).
Liu, P. et al. Double hierarchy hesitant fuzzy linguistic entropy-based TODIM approach using evidential theory. Inf. Sci. 547, 223–243 (2021).
Liu, Y., Tariq, M., Khan, S. & Abdullah, S. Complex dual hesitant fuzzy TODIM method and their application in Russia-Ukraine war’s impact on global economy. Complex Intell. Syst. 10(1), 639–653 (2024).
Tang, J., Liu, X. & Wang, W. Consensus-based generalized TODIM approach for occupational health and safety risk analysis with opinion interactions. Appl. Soft Comput. 150, 111093 (2024).
Zhang, K., Zhou, L., Dai, X. & Li, H. Stochastic group preference acceptability analysis for interval-valued multiplicative preference relations based on TODIM method. Appl. Soft Comput. 151, 111140 (2024).
Zheng, X., Wang, H., & Dai, J. A reliability analysis method for industrial robots based on double hierarchy hesitant fuzzy linguistic term set and TODIM (2023).
Wang, Z., Wei, G. & Guo, Y. TODIM method based on the CRITIC method for multi-attribute group decision making with dual probabilistic linguistic information. J. Intell. Fuzzy Syst. 43(6), 7261–7276 (2022).
Satchanska, G., Davidova, S. & Petrov, P. D. Natural and synthetic polymers for biomedical and environmental applications. Polymers 16(8), 1159 (2024).
Wang, J. et al. Amoxicillin degradation and high-value extracellular polymer recovery by algal-bacterial symbiosis systems. J. Hazard. Mater. 460, 132344 (2023).
Iakovidou, G. et al. Application of microalgae to wastewater bioremediation, with CO2 biomitigation, health product and biofuel development, and environmental biomonitoring. Appl. Sci. 14(15), 6727 (2024).
El-Sheekh, M. M., El-Kassas, H. Y. & Ali, S. S. Microalgae-based bioremediation of refractory pollutants: an approach towards environmental sustainability. Microb. Cell Fact. 24(1), 19 (2025).
Mogany, T., Bhola, V. & Bux, F. Algal-based bioplastics: global trends in applied research, technologies, and commercialization. Environ. Sci. Pollut. Res. 31(26), 38022–38044 (2024).
Schmuck, J. et al. Chlorella vulgaris-mediated Bioremediation and Valorization of Urban Wastewater, from a circular economy approach. J. Appl. Phycol. 37(3), 1795–1813 (2025).
Hadiyanto, H., Joelyna, F. A., Khoironi, A., Sudarno, S., Safaat, J. A., Pratama, W. D., & Nur, M. M. A. Harnessing Chlorella vulgaris-Aspergilus niger Interactions for Effective Microplastic Removal in Aquatic Ecosystems. Waste Biomass Valor. 1-17 (2025).
Rodriguez, R. M., Martinez, L. & Herrera, F. Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20(1), 109–119 (2011).
Gou, X. & Xu, Z. Double hierarchy linguistic term set and its extensions: the state-of-the-art survey. Int. J. Intell. Syst. 36(2), 832–865 (2021).
Oussalah, M. On the use of Hamacher’s t-norms family for information aggregation. Inf. Sci. 153, 107–154 (2003).
Zhao, H., Xu, Z. & Liu, S. Dual hesitant fuzzy information aggregation with Einstein t-conorm and t-norm. J. Syst. Sci. Syst. Eng. 26, 240–264 (2017).
Kahneman, D., & Tversky, A. Prospect theory: An analysis of decision under risk, In Handbook of the fundamentals of financial decision making: Part I (pp. 99-127) (2013).
Ahmad, M. T., Shariff, M., Yusoff, Md. F., Goh, Y. M., & Banerjee, S. Applications of microalga Chlorella vulgaris in aquaculture. Rev. Aquacult. 12(1), 328–346 (2020).
Jouanno, J. et al. Socio-ecological vulnerability assessment to Sargassum arrivals. Sci. Rep. 15(1), 9998 (2025).
Steinhagen, S. et al. Harvest time can affect the optimal yield and quality of sea lettuce (Ulva fenestrata) in a sustainable sea-based cultivation. Front. Mar. Sci. 9, 816890 (2022).
Almeida, Â., Cotas, J., Pereira, L., & Carvalho, P. Potential role of Spirogyra sp. and Chlorella sp. in bioremediation of mine drainage: A review. Phycology, 3(1), 186–201 (2023).
Ye, J. Two effective measures of intuitionistic fuzzy entropy. Computing 87(1), 55–62 (2010).
Kumar, K. & Chen, S. M. Group decision making based on weighted distance measure of linguistic intuitionistic fuzzy sets and the TOPSIS method. Inf. Sci. 611, 660–676 (2022).
Li, X., Xu, Z. & Wang, H. Three-way decisions based on some Hamacher aggregation operators under double hierarchy linguistic environment. Int. J. Intell. Syst. 36(12), 7731–7753 (2021).
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The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number RGP.2/51/46.
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Mehwish Tahir, Ahmed M. Zidan, Abdulkafi Mohammed Saeed, Ahmed A. Hamoud,Syed Inayat Ali Shah, and Saleem Abdullah, contributed equally to the conceptualization, methodology, formal analysis, investigation, writing, and revision of this manuscript. All authors have read and approved the final version of the manuscript.
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Tahir, M., Zidan, A.M., Saeed, A.M. et al. A TODIM based decision-making framework using intuitionistic double hierarchy linguistic terms for evaluating polymer absorbing algae in marine debris management. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37057-1
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DOI: https://doi.org/10.1038/s41598-026-37057-1
