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A hybrid decision-support framework for selecting sustainable domestic heating systems in cold climates
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  • Published: 11 April 2026

A hybrid decision-support framework for selecting sustainable domestic heating systems in cold climates

  • Krishnan Suvitha1,
  • Veeramuthu Murugesan2,
  • Ramasamy Jaisankar3,
  • Samayan Narayanamoorthy4,5,
  • Naif Almakayeel6,
  • Hasan Dincer7,8,10,
  • Serhat Yuksel7,9 &
  • …
  • Jeonghwan Jeon11 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Climate sciences
  • Energy science and technology
  • Engineering
  • Environmental sciences
  • Environmental social sciences
  • Mathematics and computing

Abstract

This study proposes a probabilistic hesitant fuzzy multi-criteria decision-making approach for assessing sustainable heating system alternatives under uncertain situations. The selection of heating systems is a major issue in sustainability in cold climate regions due to its high energy requirements. The proposed approach integrates the Probabilistic Hesitant Fuzzy Analytic Hierarchy Process (PHF-AHP) for determining the weights of decision criteria and the Evaluation Based on Distance from Average Solution (EDAS) for ranking alternatives. The probabilistic hesitant fuzzy approach allows decision-makers to reflect uncertainty and hesitation in decision-making under expert judgments by considering various membership values with their respective probabilities. To validate the proposed methodological framework, a case study of five heating system alternatives is presented. The results reveal that the proposed PHF-AHP-EDAS approach is reliable in ranking alternatives under ambiguity and uncertainty in sustainability decision problems.

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Data availability

The study utilizes secondary data, which are publicly available and anonymized. The datasets analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Ranjan, A. & Kanitkar, T. Energy requirements for sustainable human development. Energy Sustain. Dev. 85, 101648 (2025).

    Google Scholar 

  2. Mensi, W. et al. Dynamic frequency relationships and volatility spillovers in natural gas, crude oil, gas oil, gasoline, and heating oil markets: Implications for portfolio management. Resour. Policy 72, 102172 (2021).

    Google Scholar 

  3. Anto, D., Mehta, A. & Murti, A. Using energy as a community currency for sustainable development of newly electrified communities. Energy Sustain. Dev. 83, 101558 (2024).

    Google Scholar 

  4. Guozeng Gu and Tianmind Gao. Sustainable production of lithium salts extraction from ores in China: Cleaner production assessment. Resour. Policy 74, 102261 (2021).

    Google Scholar 

  5. Boe, V., Holden, E. & Linnerud, K. Exploring sustainable development interactions through the lens of renewable energy consumption. Energy Sustain. Dev. 86, 101708 (2025).

    Google Scholar 

  6. Zhang, S., Xu, Z. S. & He, Y. Operations and integration of probabilistic hesitant fuzzy information in decision making. Inf. Fusion 38, 1–11 (2017).

    Google Scholar 

  7. Jiang, F. J. & Ma, Q. G. Multi-attribute group decision making under probabilistic hesitant fuzzy environment with application to evaluate the transformation efficiency. Appl. Intell. 48(4), 953–965 (2018).

    Google Scholar 

  8. Li, J., Wang, J. Q. & Hu, J. H. Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information. Int. J. Mach. Learn. Cybern. 10(7), 1671–1685 (2019).

    Google Scholar 

  9. Kou, Y. Q., Feng, X. & Wang, J. A novel q-Rung Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Entropy Weights. Entropy 23(10), 1322 (2021).

    Google Scholar 

  10. Jin, F. F., Garg, H., Pei, L. D., Liu, J. P. & Chen, H. Y. Multiplicative consistency adjustment model and data envelopment analysis-driven decision-making process with probabilistic hesitant fuzzy preference relations. Int. J. Fuzzy Syst. 22(7), 2319–2332 (2020).

    Google Scholar 

  11. Liu, X. D., Wang, Z. W., Zhang, S. T. & Garg, H. An approach to probabilistic hesitant fuzzy risky multi-attribute decision making with unknown probability information. Int. J. Intell. Syst. 36(10), 5714–5740 (2021).

    Google Scholar 

  12. Qiu, Y. J., Bouraima, M. B., Badi, I., Stević, Ž & Simic, V. A decision-making model for prioritizing low-carbon policies in climate change mitigation. Chall. sustain 12(1), 1–17 (2024).

    Google Scholar 

  13. Chang, H. W., Lin, Y. L. & Wey, W. M. Advancing sustainability: Development of an ESG evaluation framework for Taiwan’s science parks. Chall. Sustain. 12(4), 255–272 (2024).

    Google Scholar 

  14. Sharma, Y. Regenerative organic agriculture: A pathway to ecosystem restoration and sustainable agricultural development. Org. Farming 11(3), 152–172 (2025).

    Google Scholar 

  15. Darko, A. et al. Review of application of analytic hierarchy process (AHP) in construction. Int. J. Constr. Manag. 19(5), 436–452 (2019).

    Google Scholar 

  16. Dos Santos, M., de Araújo Costa, I. P. & Gomes, C. F. S. Multi-criteria decision-making in the selection of warships: A new approach to the AHP method, Int. J. Anal. Hierarchy Process, 13(1), (2021).

  17. Calabrese, A., Costa, R., Levialdi, N. & Menichini, T. Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues. Technol. Forecast. Soc. Change 139, 155–168 (2019).

    Google Scholar 

  18. Zavadskas, E. K., Turskis, Z., Stevic, Z. & Mardani, A. Modelling procedure for the selection of steel pipes supplier by applying fuzzy AHP method. Oper. Res. Eng. Sci.: Theory Appl. 3(2), 39–53 (2020).

    Google Scholar 

  19. Wolnowska, A. E. & Konicki, W. Multi-criterial analysis of oversize cargo transport through the city, using the AHP method. Transp. Res. Procedia 39(614–623), 2019 (2019).

    Google Scholar 

  20. Madhu, P., Nithiyesh Kumar, C., Anojkumar, L. & Matheswaran, M. Selection of biomass materials for bio-oil yield: A hybrid multi-criteria decision making approach. Clean Technol. Environ. Policy 20(6), 1377–1384 (2018).

    Google Scholar 

  21. Ebadi Torkayesh, A., Fathipoir, F. & Saidi-Mehrabd, M. Entropy-based multi-criteria analysis of thermochemical conversions for energy recovery from municipal solid waste using fuzzy VIKOR and ELECTRE III: Case of Azerbaijan region. Iran. Journal of Energy Management and Technology 3(1), 17–29 (2019).

    Google Scholar 

  22. Wang, Z., Xu, G., Wang, H. & Ren, J. Distributed energy system for sustainability transition: A comprehensive assessment under uncertainties based on interval multi-criteria decision making method by coupling interval DEMATEL and interval VIKOR. Energy 169, 750–761 (2019).

    Google Scholar 

  23. Wei, J. & Lin, X. The multiple attribute decision-making VIKOR method and its application. International conference on wireless communications, networking and mobile computing 1(4), 2008 (2008).

    Google Scholar 

  24. Ong, M. C., Leong, Y. T., Wan, Y. K. & Chew, I. M. L. Multi-objective optimization of integrated water system by FUCOM-VIKOR approach. Process Integr. Optim. Sustain. 5(1), 43–62 (2021).

    Google Scholar 

  25. Jianxing, Y. et al. Risk assessment of submarine pipelines using modified FMEA approach based on cloud model and extended VIKOR method. Process Saf. Environ. Prot. 155, 555–574 (2021).

    Google Scholar 

  26. Khan, M. J. et al. The renewable energy source selection by remoteness index-based VIKOR method for generalized intuitionistic fuzzy soft sets. Symmetry 12(6), 977 (2020).

    Google Scholar 

  27. Ishak, A. & Nainggolan, B. Integration of fuzzy AHP-VIKOR methods in multi criteria decision making. Mater. Sci. Eng. 1003(1), 012160 (2020).

    Google Scholar 

  28. Ramavandi, B., Darabi, A. H. & Omidvar, M. Risk assessment of hot and humid environments through an integrated fuzzy AHP-VIKOR method. Stoch. Environ. Res. Risk Assess. 35(12), 2425–2438 (2021).

    Google Scholar 

  29. Wang, B., Song, J., Ren, J., Li, K. & Duan, H. Selecting sustainable energy conversion technologies for agricultural residues: A fuzzy AHP-VIKOR based prioritization from life cycle perspective. Resour. Conserv. Recycling 142, 78–87 (2019).

    Google Scholar 

  30. Oztok, M., Menlik, T., Ilham, N. I., Dahlan, N. Y. & Hussin, M. Z. Optimizing solar PV investments: A comprehensive decision-making index using CRITIC and TOPSIS. Renew. Energy Focus 49, 100551 (2024).

    Google Scholar 

  31. Chinram, R., Hussain, A., Mahmood, T. & Ali, M. I. EDAS method for multi-criteria group decision making based on intuitionistic fuzzy rough aggregation operators. IEEE Access 9, 10199–10216 (2021).

    Google Scholar 

  32. Saraswat, S. K. & Digalwar, A. K. Evaluation of energy sources based on sustainability factors using integrated fuzzy MCDM approach. Int. J. Energy Sect. Manag. 15(1), 246–266 (2021).

    Google Scholar 

  33. Hamza, M., Bafail, O. & Alidrisi, H. HVAC systems evaluation and selection for sustainable office buildings: An integrated MCDM approach. Buildings 13(7), 1847 (2023).

    Google Scholar 

  34. Wang, H. & Lahdelma, R. MCDM for sustainability ranking of district heating systems considering uncertainties. In Life Cycle Sustainability Assessment for Decision-Making 139–153 (Elsevier, 2020).

    Google Scholar 

  35. Ćesić, M., Rogulj, K., Kilić Pamuković, J. & Krtalić, A. A systematic review on fuzzy decision support systems and multi-criteria analysis in urban heat island management. Energies 17(9), 2013 (2024).

    Google Scholar 

  36. Aghazadeh, E., Yildirim, H. & Kuruoglu, M. A hybrid fuzzy MCDM methodology for optimal structural system selection compatible with sustainable materials in mass-housing projects. Sustainability 14(20), 13559 (2022).

    Google Scholar 

  37. Özdemir, Y. & Özdemir, Ş. Residential Heating System Selection Using MCDM Techniques (Design, Applications and Technology, 2020).

    Google Scholar 

  38. Wang, H., Lahdelma, R., Sahoo, B. & Debnath, B. K. A novel hybrid spherical fuzzy multi-criteria decision-making approach to select the best hydroelectric power plant source in India. Renew. Energy Focus 51, 100650 (2024).

    Google Scholar 

  39. Zhang, X., Yang, J. & Zhao, X. Optimal study of the rural house space heating systems employing the AHP and FCE methods. Energy 150, 631–641 (2018).

    Google Scholar 

  40. Amer, A. E., Rahmani, K. & Lebedev, V. A. Using the analytic hierarchy process (AHP) method for selection of phase change materials for solar energy storage applications. In Journal of Physics: Conference Series 1614(1), 012022 (2020).

    Google Scholar 

  41. Ozdemir, Y., Alcan, P., Basligil, H. & Cakrak, D. A hybrid QFD-AHP methodology and an application for heating systems in Turkey. Int. J. Optim. Control: Theor. Appl. (IJOCTA) 8(1), 117–126 (2018).

    Google Scholar 

  42. Heo, E., Kim, J. & Boo, K. J. Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renew. Sustain. Energy Rev. 14(8), 2214–2220 (2010).

    Google Scholar 

  43. Zhang, et al. Operations and integration of probabilistic hesitant fuzzy information in decision making. Inf. Fusion 38, 1–11 (2017).

  44. Jiang & Ma Multi-attribute group decision making under a probabilistic hesitant fuzzy environment with an application to evaluate the transformation efficiency,Appl. Intell., 48(4) 953–965. (2018).

  45. Hassan, I., Azmi, M. N. L., Ahmad, M. F., Nasidi, Q. Y. & Abdullah, A. T. H. The Influence of climate literacy and awareness on the utilisation of climate-related information among unskilled construction workers in Malaysia. Challenges Sustain. 13(3), 354–365 (2025).

    Google Scholar 

  46. Qiu, Y. J., Bouraima, M. B., Badi, I., Stević, Ž & Simic, V. A decision-making model for prioritizing low-carbon policies in climate change mitigation. Chall. sustain 12(1), 1–17 (2024).

    Google Scholar 

  47. Saini, D. K. J. B. et al. Deep learning-based optimized model for emotional psychological disorder activities identification in smart healthcare system. J. Res. Innov. Technol. 4, 143–157 (2025).

    Google Scholar 

  48. Inapagolla, R. K. & Babu, K. K. Overcoming Vocal Similarities in Identical Twins: A Hybrid Deep Learning Model for Emotion-Aware Speaker and Gender Recognition. Journal of Research, Innovation and Technologies, 4(1), 69-81(2025).

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Acknowledgements

This research work was supported by the National Research Foundation of Korea (NRF), by the Korea government (MSIT). The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project under Grant No. RGP2/173/46.

Funding

This work was not funded by any funding agency.

Author information

Authors and Affiliations

  1. Center for Nonlinear Systems, Chennai Institute of Technology, Chennai, India

    Krishnan Suvitha

  2. Department of Statistics, Rajah Serfoji Government College (Autonomous), Thanjavur, India

    Veeramuthu Murugesan

  3. Department of Statistics, Bharathiar University, Chennai, India

    Ramasamy Jaisankar

  4. Department of Mathematics, Bharathiar University, 641046, Coimbatore, India

    Samayan Narayanamoorthy

  5. Graduate School of Technology and Innovation Management, DGIST, 333, Techno Jungang, Daero, Hyeonpung-Eup, Dalseong-Gun, Daegu, Korea

    Samayan Narayanamoorthy

  6. Department of Industrial Engineering, College of Engineering, King Khalid University, 61421, Abha, Saudi Arabia

    Naif Almakayeel

  7. School of Business, Istanbul Medipol University, 34083, Istanbul, Turkey

    Hasan Dincer & Serhat Yuksel

  8. Department of Economics and Management, Khazar University, Baku, Azerbaijan

    Hasan Dincer

  9. Clinic of Economics, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan

    Serhat Yuksel

  10. University College, Korea University, Seoul, Republic of Korea

    Hasan Dincer

  11. Department of Industrial and Systems Engineering/Engineering Research Institute (ERI), Gyeongsang National University, 501, Jinju daero, Jinju-si, 52828, Gyeongsangnam-do, Republic of Korea

    Jeonghwan Jeon

Authors
  1. Krishnan Suvitha
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  2. Veeramuthu Murugesan
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Contributions

KS: Conceptualization, Data curation, Visualization,Formal analysis, Methodology. VM: Conceptualization, Data curation, Formal analysis, Methodology, Writing–original draft. RJ: Conceptualization, Resources, Supervision, Formal analysis, Writing–original draft. SN: Investigation, Resources, Methodology, Writing–original draft. Writing - review and Editing. NA: Formal analysis, Methodology, Validation,Funding acquisition. HD: Resources, Validation, Visualization, Writing–review and editing, Funding acquisition. SY: Validation, Writing–review and editing, Funding acquisition. JJ: Conceptualization, Investigation, Resources, Formal analysis, Methodology, Writing and Editing.

Corresponding authors

Correspondence to Samayan Narayanamoorthy or Jeonghwan Jeon.

Ethics declarations

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The authors declare no competing interests.

Ethics approval and consent to participate

This study used publicly available secondary data that did not involve human participants or patient-specific information. Therefore, approval from an institutional or licensing committee and informed consent from participants or their legal guardians were not required. All methods were conducted in accordance with relevant guidelines and regulations.

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Cite this article

Suvitha, K., Murugesan, V., Jaisankar, R. et al. A hybrid decision-support framework for selecting sustainable domestic heating systems in cold climates. Sci Rep (2026). https://doi.org/10.1038/s41598-026-47813-y

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  • Received: 03 January 2026

  • Accepted: 03 April 2026

  • Published: 11 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-47813-y

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Keywords

  • Sustainable heating systems
  • Domestic heating selection
  • Energy efficiency
  • Probabilistic hesitant fuzzy sets
  • Hybrid MCDM
  • AHP–EDAS
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