Logo PTI Logo FedCSIS

Proceedings of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 30

Towards Sustainable Transport Assessment Considering Alternative Fuels Based on MCDA Methods

,

DOI: http://dx.doi.org/10.15439/2022F144

Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 799–808 ()

Full text

Abstract. Sustainable transport can contribute to many beneficial changes, such as reducing greenhouse gas emissions and pollutants into the atmosphere, improving the country's energysecurity, and enhancing energy efficiency. Therefore, it is essential to provide a framework for reliable measurement of sustainable transport, enabling its evaluation in terms of diversity and the significance of renewable energy sources (RES). This paper presents a methodological framework for a multi-criteria assessment of sustainable transportation. The proposed framework is based on three multi-criteria decision analysis (MCDA) methods: SPOTIS (Stable Preference Ordering Towards Ideal Solution), ARAS (Additive Ratio Assessment), and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). The application of the proposed tool is demonstrated in an illustrative example of the assessment of European countries in terms of the share of alternative fuels in final energy consumption in road transport. The authors used the proposed framework to perform a comparative analysis considering three MCDA methods and two methods for determining the significance of evaluation criteria: equal and entropy weighting methods. The investigation has proven the practical suitability of the proposed tool in the problem of multi-criteria sustainable transport assessment. Furthermore, conducted analysis indicated that Sweden is characterized by the most sustainable transport in terms of significance and share of alternative fuels and RES and their diversification.

References

  1. A. Bączkiewicz, B. Kizielewicz, A. Shekhovtsov, M. Yelmikheiev, V. Kozlov, and W. Sałabun, “Comparative analysis of solar panels with determination of local significance levels of criteria using the MCDM methods resistant to the rank reversal phenomenon,” Energies, vol. 14, no. 18, p. 5727, 2021. https://doi.org/10.3390/en14185727
  2. K. G. Tsita and P. A. Pilavachi, “Decarbonizing the Greek road transport sector using alternative technologies and fuels,” Thermal Science and Engineering Progress, vol. 1, pp. 15–24, 2017. https://doi.org/10.1016/j.tsep.2017.02.003
  3. J. L. Osorio-Tejada, E. Llera-Sastresa, and S. Scarpellini, “Liquefied natural gas: Could it be a reliable option for road freight transport in the EU?” Renewable and Sustainable Energy Reviews, vol. 71, pp. 785–795, 2017. https://doi.org/10.1016/j.rser.2016.12.104
  4. J. Krause, C. Thiel, D. Tsokolis, Z. Samaras, C. Rota, A. Ward, P. Prenninger, T. Coosemans, S. Neugebauer, and W. Verhoeve, “EU road vehicle energy consumption and CO2 emissions by 2050–Expert-based scenarios,” Energy Policy, vol. 138, p. 111224, 2020. https://doi.org/10.1016/j.enpol.2019.111224
  5. C. Fernández-Dacosta, L. Shen, W. Schakel, A. Ramirez, and G. J. Kramer, “Potential and challenges of low-carbon energy options: Comparative assessment of alternative fuels for the transport sector,” Applied energy, vol. 236, pp. 590–606, 2019. https://doi.org/10.1016/j.apenergy.2018.11.055
  6. B. Djordjević and E. Krmac, “Evaluation of energy-environment efficiency of european transport sectors: non-radial DEA and TOP-SIS approach,” Energies, vol. 12, no. 15, p. 2907, 2019. https://doi.org/10.3390/en12152907
  7. A. Safari, N. Das, O. Langhelle, J. Roy, and M. Assadi, “Natural gas: A transition fuel for sustainable energy system transformation?” Energy Science & Engineering, vol. 7, no. 4, pp. 1075–1094, 2019. https://doi.org/10.1002/ese3.380
  8. D. Chiaramonti and K. Maniatis, “Security of supply, strategic storage and Covid19: Which lessons learnt for renewable and recycled carbon fuels, and their future role in decarbonizing transport?” Applied Energy, vol. 271, p. 115216, 2020. https://doi.org/10.1016/j.apenergy.2020.115216
  9. S. Pfoser, O. Schauer, and Y. Costa, “Acceptance of LNG as an alternative fuel: Determinants and policy implications,” Energy Policy, vol. 120, pp. 259–267, 2018. https://doi.org/10.1016/j.enpol.2018.05.046
  10. Z. Navas-Anguita, D. García-Gusano, and D. Iribarren, “A review of techno-economic data for road transportation fuels,” Renewable and Sustainable Energy Reviews, vol. 112, pp. 11–26, 2019. https://doi.org/10.1016/j.rser.2019.05.041
  11. J. Wątróbski, A. Bączkiewicz, E. Ziemba, and W. Sałabun, “Sustainable cities and communities assessment using the DARIA-TOPSIS method,” Sustainable Cities and Society, p. 103926, 2022. https://doi.org/10.1016/j.scs.2022.103926
  12. J. Wątróbski, A. Bączkiewicz, and W. Sałabun, “pyrepo-mcda-Reference objects based MCDA software package,” SoftwareX, vol. 19, p. 101107, 2022. https://doi.org/10.1016/j.softx.2022.101107
  13. Y. A. Solangi, C. Longsheng, and S. A. A. Shah, “Assessing and overcoming the renewable energy barriers for sustainable development in Pakistan: An integrated AHP and fuzzy TOPSIS approach,” Renewable Energy, vol. 173, pp. 209–222, 2021. https://doi.org/10.1016/j.renene.2021.03.141
  14. G. D. Oliveira and L. C. Dias, “The potential learning effect of a MCDA approach on consumer preferences for alternative fuel vehicles,” Annals of Operations Research, vol. 293, no. 2, pp. 767–787, 2020. https://doi.org/10.1007/s10479-020-03584-x
  15. W. Chmielarz and M. Zborowski, “On the Assessment of e-Banking Websites Supporting Sustainable Development Goals,” Energies, vol. 15, no. 1, p. 378, 2022. https://doi.org/10.3390/en15010378
  16. P. Ziemba, “Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods,” Energies, vol. 14, no. 22, p. 7786, 2021. https://doi.org/10.3390/en14227786
  17. A. Romero-Ania, L. Rivero Gutiérrez, and M. A. De Vicente Oliva, “Multiple criteria decision analysis of sustainable urban public transport systems,” Mathematics, vol. 9, no. 16, p. 1844, 2021. https://doi.org/10.3390/math9161844
  18. L. Rivero Gutiérrez, M. A. De Vicente Oliva, and A. Romero-Ania, “Economic, Ecological and Social Analysis Based on DEA and MCDA for the Management of the Madrid Urban Public Transportation System,” Mathematics, vol. 10, no. 2, p. 172, 2022. https://doi.org/10.3390/math10020172
  19. J. L. Osorio-Tejada, E. Llera-Sastresa, and S. Scarpellini, “A multicriteria sustainability assessment for biodiesel and liquefied natural gas as alternative fuels in transport systems,” Journal of Natural Gas Science and Engineering, vol. 42, pp. 169–186, 2017. https://doi.org/10.1016/j.jngse.2017.02.046
  20. M. A. Hatefi, “A Multi-Criteria Decision Analysis Model on the Fuels for Public Transport, with the Use of Hybrid ROC-ARAS Method,” Petroleum Business Review, vol. 2, no. 1, pp. 45–55, 2018. https://dx.doi.org/10.22050/pbr.2018.77848
  21. J. Wątróbski, J. Jankowski, and Z. Piotrowski, “The selection of multicriteria method based on unstructured decision problem description,” in International Conference on Computational Collective Intelligence. Springer, 2014. https://doi.org/10.1007/978-3-319-11289-3_46 pp. 454–465.
  22. J. Jankowski, K. Kolomvatsos, P. Kazienko, and J. Wątróbski, “Fuzzy modeling of user behaviors and virtual goods purchases in social networking platforms,” Journal of Universal Computer Science, vol. 22, no. 3, pp. 416–437, 2016. http://dx.doi.org/10.3217/jucs-022-03-0416
  23. J. Dezert, A. Tchamova, D. Han, and J.-M. Tacnet, “The spotis rank reversal free method for multi-criteria decision-making support,” in 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE, 2020. https://doi.org/10.23919/FUSION45008.2020.9190347 pp. 1–8.
  24. J. Jankowski, W. Sałabun, and J. Wątróbski, “Identification of a multicriteria assessment model of relation between editorial and commercial content in web systems,” in Multimedia and Network Information Systems. Springer, 2017, pp. 295–305.
  25. S. Goswami and S. Mitra, “Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology,” International Journal of Data and Network Science, vol. 4, no. 1, pp. 27–42, 2020. http://dx.doi.org/10.5267/j.ijdns.2019.8.004
  26. B. Bera, P. K. Shit, N. Sengupta, S. Saha, and S. Bhattacharjee, “Susceptibility of deforestation hotspots in Terai-Dooars belt of Himalayan Foothills: A comparative analysis of VIKOR and TOPSIS models,” Journal of King Saud University-Computer and Information Sciences, 2021. https://doi.org/10.1016/j.jksuci.2021.10.005
  27. J. Martins and F. Brito, “Alternative fuels for internal combustion engines,” Energies, vol. 13, no. 16, p. 4086, 2020. https://doi.org/10.3390/en13164086
  28. M. Sajjad, W. Sałabun, S. Faizi, M. Ismail, and J. Wątróbski, “Statistical and analytical approach of multi-criteria group decision-making based on the correlation coefficient under intuitionistic 2-tuple fuzzy linguistic environment,” Expert Systems with Applications, vol. 193, p. 116341, 2022. https://doi.org/10.1016/j.eswa.2021.116341
  29. Eurostat, Final energy consumption in road transport by type of fuel, 2022. [Online]. Available: https://ec.europa.eu/eurostat/databrowser/view/ten00127/default/table?lang=en
  30. J. Wątróbski, J. Jankowski, P. Ziemba, A. Karczmarczyk, and M. Zioło, “Generalised framework for multi-criteria method selection,” Omega, vol. 86, pp. 107–124, 2019. https://doi.org/10.1016/j.omega.2018.07.004
  31. E. Ziemba, “The contribution of ICT adoption to sustainability: Households’ perspective,” Information Technology & People, vol. 32, no. 3, pp. 731–753, 2019. https://doi.org/10.1108/ITP-02-2018-0090
  32. A. Bączkiewicz, B. Kizielewicz, A. Shekhovtsov, J. Wątróbski, and W. Sałabun, “Methodical Aspects of MCDM Based E-Commerce Recommender System,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 16, no. 6, pp. 2192–2229, 2021. https://doi.org/10.3390/jtaer16060122
  33. E. Ziemba, “The contribution of ICT adoption to the sustainable information society,” Journal of Computer Information Systems, vol. 59, no. 2, pp. 116–126, 2019. https://doi.org/10.1080/08874417.2017.1312635
  34. N. C. Onat, “How to compare sustainability impacts of alternative fuel Vehicles?” Transportation Research Part D: Transport and Environment, vol. 102, p. 103129, 2022. https://doi.org/10.1016/j.trd.2021.103129
  35. A. Lindfors, R. Feiz, M. Eklund, and J. Ammenberg, “Assessing the potential, performance and feasibility of urban solutions: methodological considerations and learnings from biogas solutions,” Sustainability, vol. 11, no. 14, p. 3756, 2019. https://doi.org/10.3390/su11143756
  36. S. Dahlgren and J. Ammenberg, “Sustainability Assessment of Public Transport, Part II—Applying a Multi-Criteria Assessment Method to Compare Different Bus Technologies,” Sustainability, vol. 13, no. 3, p. 1273, 2021. https://doi.org/10.3390/su13031273
  37. J. Ammenberg and S. Dahlgren, “Sustainability Assessment of Public Transport, Part I—A Multi-Criteria Assessment Method to Compare Different Bus Technologies,” Sustainability, vol. 13, no. 2, p. 825, 2021. https://doi.org/10.3390/su13020825
  38. W. Chmielarz and M. Zborowski, “Towards sustainability in E-banking website assessment methods,” Sustainability, vol. 12, no. 17, p. 7000, 2020. https://doi.org/10.3390/su12177000