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Review of PROMETHEE method in transportation

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In recent decades, decision support system has been constantly growing in the field of transportation planning. PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation) method is an efficient decision-making support deployed in case of a finite number of criteria. It provides a partial ranking through PROMETHEE I and a complete ranking with PROMETHEE II. This outranking methodology is characterized by the elimination of scale effects between criteria and managing incomparability with the comprehensive ranking. However, PROMETHEE does not provide guidance to assign weights to criteria and assumes that decision makers are able to allocate weights. This review presents an overview of PROMETHEE models applied in transportation and points out the found gaps in literature.
Słowa kluczowe
Rocznik
Strony
69--74
Opis fizyczny
Bibliogr. 29 poz., tab.
Twórcy
  • Budapest University of Technology and Economics, Stoczek u. 2, H-1111 Budapest, Hungary
  • Budapest University of Technology and Economics, Stoczek u. 2, H-1111 Budapest, Hungary
Bibliografia
  • 1. Alkharabsheh, A., Moslem, S., Duleba, S., 2019, Evaluating passenger demand for development of the urban transport system by an AHP model with the real-world application of Amman, Applied Sciences (Switzerland), 9(22). DOI: 10.3390/app9224759
  • 2. Anagnostopoulos, K., Giannopoulou, M., Roukounis, Y., 2003. Multicriteria evaluation of transportation infrastructure projects: An application of PRO-METHEE and GAIA methods, Advances in Transport, 14, 599-608, DOI: 10.2495/UT030591
  • 3. Arcidiacono, S.G., Greco, P.S., 2018. Robustness Analysis for Interacting Criteria in Advanced Decision Support Systems, niversity of Catania and University of Messina. Available at: https://iris.unime.it/retrieve/handle/11570/3131327/214741/PhD Thesis Arcidiacono Sally Giuseppe.pdf.
  • 4. Babaee, S. et al., 2015. Use of DEA and PROMETHEE II to assess the performance of older drivers, Transportation Research Procedia, 10(July), 798-808. DOI: 10.1016/j.trpro.2015.09.033
  • 5. Bagherikahvarin, M., De Smet, Y., 2017. Determining new possible weight values in PROMETHEE: A procedure based on data envelopment analysis, Journal of the Operational Research Society, 68(5), 484-495. DOI: 10.1057/s41274-016-0107-1
  • 6. Balali, V. et al., 2014. Selection of appropriate material, construction technique, and structural system of bridges by use of multicriteria decision-making method, Transportation Research Record, 2431(1), 79-87, DOI: 10.3141/2431-11
  • 7. Bilişik, Ö.N. et al., 2013. A hybrid fuzzy methodology to evaluate customer satisfaction in a public transportation system for Istanbul, Total Quality Management and Business Excellence, 24(9-10), 1141-1159. DOI: 10.1080/14783363.2013.809942
  • 8. Brans, J.P., De Smet, Y., 2016. PROMETHEE Methods, Multiple Criteria Decision Analysis, DOI: 10.1007/978-1-4939-3094-4
  • 9. Brans, J.P. Mareschal, B.. 1994. The PROMCALC & GAIA decision support system for multicriteria decision aid, Decision Support Systems, 12(4–5), 297-310, DOI: 10.1016/0167-9236(94)90048-5
  • 10.Brans, J.P., Vincke, P. and Mareschal, B., 1986. How to select and how to rank projects: The Promethee method, European Journal of Operational Research, 24(2), 228238. DOI: 10.1016/0377-2217(86)90044-5
  • 11. Dağdeviren, M., 2008. Decision making in equipment selection: An integrated approach with AHP and PROMETHEE, Journal of Intelligent Manufacturing, 19(4), 397-406, DOI: 10.1007/s10845-008-0091-7,
  • 12. Elevli, B., Demirci, A., 2004. Multicriteria choice of ore transport system for an underground mine: Application of PROMETHEE methods, Journal of The South African Institute of Mining and Metallurgy, 104(5), 251-256.
  • 13. Fernández-Castro, A.S., Jiménez, M., 2005. PROMETHEE: An extension through fuzzy mathematical programming, Journal of the Operational Research Society, 56(1), 119-122, DOI: 10.1057/palgrave.jors.2601828
  • 14. Gunawardena, J. et al., 2015. Sources and transport pathways of common heavy metals to urban road surfaces, Ecological Engineering, 77, 98-102. DOI: 10.1016/j.ecoleng.2015.01.023
  • 15. Hensher, D.A., Ho, C.Q., Reck, D.J., 2021. Mobility as a service and private car use: Evidence from the Sydney MaaS trial, Transportation Research Part A: Policy and Practice, 145, 17-33, DOI: 10.1016/j.tra.2020.12.015
  • 16. Ishizaka, A. et al., 2020. Examining knowledge transfer activities in UK universities: advocating a PROMETHEE-based approach’, International Journal of Entrepreneurial Behaviour and Research, 26(6), 1389-1409. DOI: 10.1108/IJEBR-01-2020-0028
  • 17. Ishizaka, A., Resce, G., 2020. Best-Worst PROMETHEE method for evaluating school performance in the OECD’s PISA project, Socio-Economic Planning Sciences, (May), DOI: 10.1016/j.seps.2020.100799
  • 18. Kabir, G., Sumi, R.S., 2014. Integrating fuzzy analytic hierarchy process with PROMETHEE method for total quality management consultant selection, Production and Manufacturing Research, 2(1), 380-399. DOI: 10.1080/21693277.2014.895689
  • 19. Kabir, G., Sumi, R.S., 2015. Hazardous waste transportation firm selection using fuzzy analytic hierarchy and PROMETHEE methods, International Journal of Shipping and Transport Logistics, 7(2), 115-136, DOI: 10.1504/IJSTL.2015.067847
  • 20. van Lierop, D., El-Geneidy, A., 2016. Enjoying loyalty: The relationship between service quality, customer satisfaction, and behavioral intentions in public transit, Research in Transportation Economics, 59, 50-59, DOI: 10.1016/j.retrec.2016.04.001
  • 21. Lolli, F. et al., 2016, Waste treatment: an environmental, economic and social analysis with a new group fuzzy PROMETHEE approach, Clean Technologies and Environmental Policy, 18(5), 1317-1332 DOI: 10.1007/s10098-015-1087-6.
  • 22. Macharis, C. et al., 1998, The GDSS PROMETHEE procedure - A PROMETHEE-GAIA based procedure for group decision support, Journal of Decision Systems, 7(May 2014), 283-307, Available at: httpideas.repec.orgpulbulbeco2013-9373.html
  • 23. Macharis, C. et al., 2004. PROMETHEE and AHP: The design of operational synergies in multicriteria analysis - Strengthening PROMETHEE with ideas of AHP, European Journal of Operational Research, 153(2), 307-317, DOI: 10.1016/S0377-2217(03)00153-X
  • 24. Moslem, S. et al., 2019. Analysing Stakeholder Consensus for a Sustainable Transport Development Decision by the Fuzzy AHP and Interval AHP, Sustainability, 11(12), 3271, DOI: 10.3390/su11123271
  • 25. Shen, W., Xiao, W., Wang, X., 2016. Passenger satisfaction evaluation model for Urban rail transit: A structural equation modeling based on partial least squares, Transport Policy, 46, 20–31, DOI: 10.1016/j.tranpol.2015.10.006
  • 26. Tsamboulas, D.A., 2007. A tool for prioritizing multinational transport infrastructure investments, Transport Policy, 14(1), 11-26, DOI: 10.1016/j.tranpol.2006.06.001
  • 27. Turcksin, L., Bernardini, A., Macharis, C., 2011. A combined AHPPROMETHEE approach for selecting the most appropriate policy scenario to stimulate a clean vehicle fleet, Procedia - Social and Behavioral Sciences, 20, 954-965, DOI: 10.1016/j.sbspro.2011.08.104
  • 28. Wang, J.J., Yang, D.L., 2006. Using a hybrid multi-criteria decision aid method for information systems outsourcing, Computers and Operations Research, 34(12), 3691-3700 DOI: 10.1016/j.cor.2006.01.017
  • 29. Zuo, C. et al., 2018. Reducing carbon emissions related to the transportation of aggregates: Is road or rail the solution?, Transportation Research Part A: Policy and Practice, 117(July), 26-38, DOI: 10.1016/j.tra.2018.08.006
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-13630b4f-f489-48ef-8232-ddce35028967
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