Share:


Applications of the MOORA and TOPSIS methods for decision of electric vehicles in public transportation technology

Abstract

The technological development of buses among the new alternative concepts is evaluated in this paper. Bus transportation is an important system in the public transportation, which is cheap, flexible and, in many cases, in terms of capacity and speed. But increasing car traffic in the city centre and increasing the emission such as Carbon Dioxide (CO2) in the air are some of the dangerous problems for urban life. Therefore, it is needed the public transportation to stop increasing car traffic and needed the cleaner technology for air and environmental quality. Electric Buses (EBs) can play an important role for resident’s life quality with improving the urban air quality. However, planners and managers have difficulty in decision-making due to diversified EBs together with the developing technology. Multi-criteria decision-making (MCDM) methods that are analytic decision processes, prepare a good solution for this problem. In this study, 5 EBs are assessed under the special criteria with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Multi‐Objective Optimization on the basis of the Ratio Analysis (MOORA) methods. These 2 methods are MCDM methods that are used to aim of ranking of alternatives in the complex decision problem. These methods are applied to select the best EB under the 6 criteria. Finally, E5-Bus is selected as the best option that rank of the 1st at all the 3 methods. Besides, MOORA and TOPSIS methods were compared. The results are shown alongside the best bus selection for public transportation that MOORA method is also a strong tool for solving vehicle selection problems in transportation. The proposed model has been validated using existing real applications. The proposed multi-criteria analysis can be used for advising decision-makers in their decision-making process for Electric Vehicles (EVs) in the area of clean transportation.

Keyword : electric bus, MOORA, TOPSIS, urban transportation, MCDM, selection process

How to Cite
Hamurcu, M., & Eren, T. (2022). Applications of the MOORA and TOPSIS methods for decision of electric vehicles in public transportation technology. Transport, 37(4), 251–263. https://doi.org/10.3846/transport.2022.17783
Published in Issue
Nov 18, 2022
Abstract Views
1039
PDF Downloads
786
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Adalı, E. A.; Işık, A. T. 2017. The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem, Journal of Industrial Engineering International 13(2): 229–237. https://doi.org/10.1007/s40092-016-0175-5

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 9(22): 4759. https://doi.org/10.3390/app9224759

Altuntas, S.; Dereli, T.; Yilmaz, M. K. 2015. Evaluation of excavator technologies: application of data fusion based MULTIMOORA methods, Journal of Civil Engineering and Management 21(8): 977–997. https://doi.org/10.3846/13923730.2015.1064468

Andrenacci, N.; Ragona, R.; Valenti, G. 2016. A demand-side approach to the optimal deployment of electric vehicle charging stations in metropolitan areas, Applied Energy 182: 39–46. https://doi.org/10.1016/j.apenergy.2016.07.137

Awasthi, A.; Chauhan, S. S.; Omrani, H. 2011a. Application of fuzzy TOPSIS in evaluating sustainable transportation systems, Expert Systems with Applications 38(10): 12270–12280. https://doi.org/10.1016/j.eswa.2011.04.005

Awasthi, A.; Chauhan, S. S.; Omrani, H.; Panahi, A. 2011b. A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality, Computers & Industrial Engineering 61(3): 637–646. https://doi.org/10.1016/j.cie.2011.04.019

Awasthi, A.; Govindan, K.; Gold, S. 2018. Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach, International Journal of Production Economics 195: 106–117. https://doi.org/10.1016/j.ijpe.2017.10.013

Awasthi, A.; Venkitusamy, K.; Padmanaban, S.; Selvamuthukumaran, R.; Blaabjerg, F.; Singh, A. K. 2017. Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm, Energy 133: 70–78. https://doi.org/10.1016/j.energy.2017.05.094

Aydın, S.; Kahraman, C. 2014. Vehicle selection for public transportation using an integrated multi criteria decision making approach: a case of Ankara, Journal of Intelligent & Fuzzy Systems 26(5): 2467–2481. https://doi.org/10.3233/IFS-130917

Baležentis, A.; Baležentis, T. 2011. Assessing the efficiency of Lithuanian transport sector by applying the methods of MULTIMOORA and data envelopment analysis, Transport 26(3): 263–270. https://doi.org/10.3846/16484142.2011.621146

Brans, J. P.; Vincke, P. 1985. A preference ranking organisation method, Management Science 31(6): 647–656. https://doi.org/10.1287/mnsc.31.6.647

Brauers, W. K. M.; Zavadskas, E. K. 2012. Robustness of MULTIMOORA: a method for multi-objective optimization, Informatica 23(1): 1–25. https://doi.org/10.15388/Informatica.2012.346

Brauers, W. K.; Zavadskas, E. K. 2009. Robustness of the multi‐objective MOORA method with a test for the facilities sector, Technological and Economic Development of Economy 15(2): 352–375. https://doi.org/10.3846/1392-8619.2009.15.352-375

Brauers, W. K. M.; Zavadskas, E. K. 2006. The MOORA method and its application to privatization in a transition economy, Control and Cybernetics 35(2): 445–469.

Brauers, W. K. M.; Zavadskas, E. K.; Peldschus, F.; Turskis, Z. 2008. Multi-objective optimization of road design alternatives with an application of the MOORA method, in ISARC 2008: the 25th International Symposium on Automation and Robotics in Construction, 26–29 June 2008, Vilnius, Lithuania, 541–548.

Brauers, W. K. M.; Zavadskas, E. K.; Turskis, Z.; Vilutienė, T. 2008. Multi‐objective contractor’s ranking by applying the MOORA method, Journal of Business Economics and Management 9(4): 245–255. https://doi.org/10.3846/1611-1699.2008.9.245-255

Buwana, E.; Hasibuan, H. S.; Abdini, C. 2016. Alternatives selection for sustainable transportation system in Kasongan city, Procedia – Social and Behavioral Sciences 227: 11–18. https://doi.org/10.1016/j.sbspro.2016.06.037

Büyüközkan, G.; Feyzioğlu, O.; Göçer, F. 2018. Selection of sustainable urban transportation alternatives using an integrated intuitionistic fuzzy Choquet integral approach, Transportation Research Part D: Transport and Environment 58: 186–207. https://doi.org/10.1016/j.trd.2017.12.005

Canals Casals, L.; Martinez-Laserna, E.; Amante García, B.; Nieto, N. 2016. Sustainability analysis of the electric vehicle use in Europe for CO2 emissions reduction, Journal of Cleaner Production 127: 425–437. https://doi.org/10.1016/j.jclepro.2016.03.120

Celik, E.; Akyuz, E. 2018. An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: the case of ship loader, Ocean Engineering, 155: 371–381. https://doi.org/10.1016/j.oceaneng.2018.01.039

Chiranjeevi, M.; Ashok Kumar, D. V.; Kiranmayi, R. 2020. An investigation of li-ion battery performance for AC drives used in electric vehicular technology, Lecture Notes in Electrical Engineering 569: 213–221. https://doi.org/10.1007/978-981-13-8942-9_19

Choma, E. F.; Ugaya, C. M. L. 2017. Environmental impact assessment of increasing electric vehicles in the Brazilian fleet, Journal of Cleaner Production 152: 497–507. https://doi.org/10.1016/j.jclepro.2015.07.091

Curiel-Esparza, J.; Mazario-Diez, J. L.; Canto-Perello, J.; Martin-Utrillas, M. 2016. Prioritization by consensus of enhancements for sustainable mobility in urban areas, Environmental Science & Policy 55: 248–257. https://doi.org/10.1016/j.envsci.2015.10.015

Çalışkan, H.; Kurşuncu, B.; Kurbanoğlu, C.; Güven, Ş. Y. 2013. Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods, Materials & Design 45: 473–479. https://doi.org/10.1016/j.matdes.2012.09.042

Das, M. C.; Pandey, A.; Mahato, A. K.; Singh, R. K. 2019. Comparative performance of electric vehicles using evaluation of mixed data, OPSEARCH 56(3): 1067–1090. https://doi.org/10.1007/s12597-019-00398-9

De Aquino, J. T.; De Melo, F. J. C.; De Barros Jerônimo, T.; De Medeiros, D. D. 2019. Evaluation of quality in public transport services: the use of quality dimensions as an input for fuzzy TOPSIS, International Journal of Fuzzy Systems 21(1): 176–193. https://doi.org/10.1007/s40815-018-0524-1

De Luca, S. 2014. Public engagement in strategic transportation planning: an analytic hierarchy process based approach, Transport Policy 33: 110–124. https://doi.org/10.1016/j.tranpol.2014.03.002

Dey, B.; Bairagi, B.; Sarkar, B.; Sanyal, S. 2012. A MOORA based fuzzy multi-criteria decision making approach for supply chain strategy selection, International Journal of Industrial Engineering Computations 3(4): 649–662. https://doi.org/10.5267/j.ijiec.2012.03.001

Dey, B.; Bairagi, B.; Sarkar, B; Sanyal, S. K. 2016. Multi objective performance analysis: a novel multi-criteria decision making approach for a supply chain, Computers & Industrial Engineering 94: 105–124. https://doi.org/10.1016/j.cie.2016.01.019

Ding, X.; Zhong, J. 2018. Power battery recycling mode selection using an extended MULTIMOORA method, Scientific Programming 2018: 7675094. https://doi.org/10.1155/2018/7675094

Dizdar, E. N.; Ünver, M. 2020. The assessment of occupational safety and health in Turkey by applying a decision-making method; MULTIMOORA, Human and Ecological Risk Assessment: an International Journal 26(6): 1–12. https://doi.org/10.1080/10807039.2019.1600399

Ensslen, A.; Schücking, M.; Jochem, P.; Steffens, H.; Fichtner, W.; Wollersheim, O.; Stella, K. 2017. Empirical carbon dioxide emissions of electric vehicles in a French-German commuter fleet test, Journal of Cleaner Production 142: 263–278. https://doi.org/10.1016/j.jclepro.2016.06.087

Ercan, T.; Zhao, Y.; Tatari, O.; Pazour, J. A. 2015. Optimization of transit bus fleet’s life cycle assessment impacts with alternative fuel options, Energy 93: 323–334. https://doi.org/10.1016/j.energy.2015.09.018

Erdogan, S.; Sayin, C. 2018. Selection of the most suitable alternative fuel depending on the fuel characteristics and price by the hybrid MCDM method, Sustainability 10(5): 1583. https://doi.org/10.3390/su10051583

Eren, T.; Gür, Ş. 2017. Online alişveriş siteleri için AHP ve TOPSIS yöntemleri ile 3PL firma seçimi, Hitit Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 10(2): 819–834. https://doi.org/10.17218/hititsosbil.285102 (in Turkish).

Erdoğan, M.; Kaya, İ. 2016. Evaluating alternative-fuel busses for public transportation in istanbul using interval type-2 fuzzy AHP and TOPSIS, Journal of Multiple-Valued Logic and Soft Computing 26(6): 625–642.

Errampalli, M.; Patil, K. S.; Prasad, C. S. R. K. 2020. Evaluation of integration between public transportation modes by developing sustainability index for Indian cities, Case Studies on Transport Policy 8(1): 180–187. https://doi.org/10.1016/j.cstp.2018.09.005

Fotouhi, A.; Auger, D. J.; Propp, K.; Longo, S.; Wild, M. 2016. A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur, Renewable and Sustainable Energy Reviews 56: 1008–1021. https://doi.org/10.1016/j.rser.2015.12.009

Gadakh, V. S.; Shinde, V. B.; Khemnar, N. S.; Kumar, A. 2018. Application of MOORA method for friction stir welding tool material selection, in ICATSA 2016: Techno-Societal 2016, International Conference on Advanced Technologies for Societal Applications, 20–21 December 2016, Pandharpur, India, 845–854. https://doi.org/10.1007/978-3-319-53556-2_86

Gilbert, R.; Irwin, N.; Hollingworth, B.; Blais, P. 2003. Sustainable Transportation Performance Indicators (STPI). Project Report on Phase 3. The Centre for Sustainable Transportation, Toronto, Canada. 125 p.

Guo, S.; Zhao, H. 2015. Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective, Applied Energy 158: 390–402. https://doi.org/10.1016/j.apenergy.2015.08.082

Gupta, H. 2018. Evaluating service quality of airline industry using hybrid best worst method and VIKOR, Journal of Air Transport Management 68: 35–47. https://doi.org/10.1016/j.jairtraman.2017.06.001

Güner, S. 2018. Measuring the quality of public transportation systems and ranking the bus transit routes using multi-criteria decision making techniques, Case Studies on Transport Policy 6(2): 214–224. https://doi.org/10.1016/j.cstp.2018.05.005

Hafezalkotob, Ar.; Hafezalkotob, As.; Liao, H.; Herrera, F. 2019. An overview of MULTIMOORA for multi-criteria decision-making: theory, developments, applications, and challenges, Information Fusion 51: 145–177. https://doi.org/10.1016/j.inffus.2018.12.002

Hamurcu, M.; Eren, T. 2019. An application of multicriteria decision-making for the evaluation of alternative monorail routes, Mathematics 7(1): 16. https://doi.org/10.3390/math7010016

Hamurcu, M.; Eren, T. 2018. Multi-objective optimization using MOORA method for development of urban transportation, in TRANSIST: Istanbul Transportation Congress and Fair, 8–10 November 2018, Istanbul, Turkey.

Hamurcu, M.; Eren, T. 2017. Selection of monorail technology by using multicriteria decision making, Sigma: Journal of Engineering and Natural Sciences 8(4): 303–314. Available from Internet: https://sigma.yildiz.edu.tr/article/571

Hidrue, M. K.; Parsons, G. R.; Kempton, W.; Gardner, M. P. 2011. Willingness to pay for electric vehicles and their attributes, Resource and Energy Economics 33(3): 686–705. https://doi.org/10.1016/j.reseneeco.2011.02.002

Hsiao, H.; Chan, Y.-C.; Chiang, C.-H.; Tzeng, G.-H. 2005. Fuzzy AHP and TOPSIS for selecting low pollutant emission bus systems, in Globalization of Energy: Markets, Technology, and Sustainability: 28th IAEE International Conference, 3–6 June 2005, Taipei, Taiwan, 1–19.

Hwang, C.-L.; Yoon, K. 1981. Multiple Attribute Decision Making: Methods and Applications a State-of-the-Art Survey. Springer. 269 p. https://doi.org/10.1007/978-3-642-48318-9

Jochem, P.; Doll, C.; Fichtner, W. 2016. External costs of electric vehicles, Transportation Research Part D: Transport and Environment 42: 60–76. https://doi.org/10.1016/j.trd.2015.09.022

Jones, S.; Tefe, M.; Appiah-Opoku, S. 2013. Proposed framework for sustainability screening of urban transport projects in developing countries: a case study of Accra, Ghana, Transportation Research Part A: Policy and Practice 49: 21–34. https://doi.org/10.1016/j.tra.2013.01.003

Karande, P.; Chakraborty, S. 2012. Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection, Materials & Design 37: 317–324. https://doi.org/10.1016/j.matdes.2012.01.013

Khayamim, R.; Shetab-Boushehri, S.-N.; Hosseininasab, S.-M.; Karimi, H. 2020. A sustainable approach for selecting and timing the urban transportation infrastructure projects in large-scale networks: a case study of Isfahan, Iran, Sustainable Cities and Society 53: 101981. https://doi.org/10.1016/j.scs.2019.101981

Kecek, G.; Demirağ, F. 2016. A comparative analysis of TOPSIS and MOORA in laptop selection, Research on Humanities and Social Sciences 6(14): 1–9.

Kong, C.; Jovanovic, R.; Bayram, I. S.; Devetsikiotis, M. 2017. A hierarchical optimization model for a network of electric vehicle charging stations, Energies 10(5): 675. https://doi.org/10.3390/en10050675

Kumar, A.; Aswin, A.; Gupta, H. 2020. Evaluating green performance of the airports using hybrid BWM and VIKOR methodology, Tourism Management 76: 103941. https://doi.org/10.1016/j.tourman.2019.06.016

Lane, B.; Potter, S. 2007. The adoption of cleaner vehicles in the UK: exploring the consumer attitude – action gap, Journal of Cleaner Production 15(11–12): 1085–1092. https://doi.org/10.1016/j.jclepro.2006.05.026

Lanjewar, P. B.; Rao, R. V.; Kale, A. V. 2015. Assessment of alternative fuels for transportation using a hybrid graph theory and analytic hierarchy process method, Fuel 154: 9–16. https://doi.org/10.1016/j.fuel.2015.03.062

Li, C.; Negnevitsky, M.; Wang, X.; Yue, W. L.; Zou, X. 2019. Multi-criteria analysis of policies for implementing clean energy vehicles in China, Energy Policy 129: 826–840. https://doi.org/10.1016/j.enpol.2019.03.002

Li, Y.; Zhao, L.; Suo, J. 2014. Comprehensive assessment on sustainable development of highway transportation capacity based on entropy weight and TOPSIS, Sustainability 6(7): 4685–4693. https://doi.org/10.3390/su6074685

Lin, M.; Huang, C.; Xu, Z. 2020. MULTIMOORA based MCDM model for site selection of car sharing station under picture fuzzy environment, Sustainable Cities and Society 53: 101873. https://doi.org/10.1016/j.scs.2019.101873

Litman, T. 2008. Valuing transit service quality improvements, Journal of Public Transportation 11(2): 43–63. https://doi.org/10.5038/2375-0901.11.2.3

Mahadik, Y.; Vadirajacharya, K. 2019. Battery life enhancement in a hybrid electrical energy storage system using a multi-source inverter, World Electric Vehicle Journal 10(2): 17. https://doi.org/10.3390/wevj10020017

Majumder, H.; Maity, K. 2017. Optimization of machining condition in WEDM for titanium grade 6 using MOORA coupled with PCA – a multivariate hybrid approach, Journal of Advanced Manufacturing Systems 16(2): 81–99. https://doi.org/10.1142/S0219686717500068

Mandal, U. K.; Sarkar, B. 2012. Selection of best intelligent manufacturing system (IMS) under fuzzy MOORA conflicting MCDM Environment, International Journal of Emerging Technology and Advanced Engineering 2(9): 301–310.

Mahmoudi, R.; Shetab-Boushehri, S.-N.; Hejazi, S. R.; Emrouznejad, A. 2019. Determining the relative importance of sustainability evaluation criteria of urban transportation network, Sustainable Cities and Society 47: 101493. https://doi.org/10.1016/j.scs.2019.101493

Mohammadi, A.; Amador-Jimenez, L.; Nasiri, F. 2020. A multi-criteria assessment of the passengers’ level of comfort in urban railway rolling stock, Sustainable Cities and Society 53: 101892. https://doi.org/10.1016/j.scs.2019.101892

Mukherjee, S. 2017. Selection of alternative fuels for sustainable urban transportation under multi-criteria intuitionistic fuzzy environment, Fuzzy Information and Engineering 9(1): 117–135. https://doi.org/10.1016/j.fiae.2017.03.006

Nordelöf, A.; Messagie, M.; Tillman, A.-M.; Söderman, M. L.; Van Mierlo, J. 2014. Environmental impacts of hybrid, plug-in hybrid, and battery electric vehicles – what can we learn from life cycle assessment?, The International Journal of Life Cycle Assessment 19(11): 1866–1890. https://doi.org/10.1007/s11367-014-0788-0

Nosal, K.; Solecka, K. 2014. Application of AHP method for multi-criteria evaluation of variants of the integration of urban public transport, Transportation Research Procedia 3: 269–278. https://doi.org/10.1016/j.trpro.2014.10.006

Noureddine, M.; Ristic, M. 2019. Route planning for hazardous materials transportation: multicriteria decision making approach, Decision Making: Applications in Management and Engineering 2(1): 66–85.

Onat, N. C.; Gumus, S.; Kucukvar, M.; Tatari, O. 2016. Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies, Sustainable Production and Consumption 6: 12–25. https://doi.org/10.1016/j.spc.2015.12.003

Opricovic, S.; Tzeng, G.-H. 2007. Extended VIKOR method in comparison with outranking methods, European Journal of Operational Research 178(2): 514–529. https://doi.org/10.1016/j.ejor.2006.01.020

Oztaysi, B.; Onar, S. C.; Kahraman, C.; Yavuz, M. 2017. Multi-criteria alternative-fuel technology selection using interval-valued intuitionistic fuzzy sets, Transportation Research Part D: Transport and Environment 53: 128–148. https://doi.org/10.1016/j.trd.2017.04.003

Özbek, A. 2015. Efficiency analysis of foreign-capital banks in turkey by OCRA and MOORA, Research Journal of Finance and Accounting 6(13): 21–30. Available from Internet: https://www.iiste.org/Journals/index.php/RJFA/article/view/24328

Özcan, E.; Danışan, T.; Eren, T. 2019. A mathematical model proposal for maintenance strategies optimization of the most critical electrical equipment groups of hydroelectric power plants, Pamukkale University Journal of Engineering Sciences 25(4): 498–506. https://doi.org/10.5505/pajes.2018.38455

Özcan, E.; Özder, E. H.; Eren, T. 2018. Supplier selection with AHP–TOPSIS combination in natural gas combined cycle power plant, Journal of Trends in the Development of Machinery and Associated Technology 21(1): 57–60. Available from Internet: http://tmt.unze.ba/zbornik/TMT2018Journal/15.pdf

Özcan, E. C.; Ünlüsoy, S.; Eren, T. 2017. A combined goal programming – AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants, Renewable and Sustainable Energy Reviews 78: 1410–1423. https://doi.org/10.1016/j.rser.2017.04.039

Pedroso, G.; Bermann, C.; Sanches-Pereira, A. 2018. Combining the functional unit concept and the analytic hierarchy process method for performance assessment of public transport options, Case Studies on Transport Policy 6(4): 722–736. https://doi.org/10.1016/j.cstp.2018.09.002

Rezaei, J. 2015. Best-worst multi-criteria decision-making method, Omega 53: 49–57. https://doi.org/10.1016/j.omega.2014.11.009

Rezvani, Z.; Jansson, J.; Bodin, J. 2015. Advances in consumer electric vehicle adoption research: a review and research agenda, Transportation Research Part D: Transport and Environment 34: 122–136. https://doi.org/10.1016/j.trd.2014.10.010

Roy, B. 1990. The outranking approach and the foundations of ELECTRE methods, in C. A. Bana e Costa (Ed.). Readings in Multiple Criteria Decision Aid, 155–183. https://doi.org/10.1007/978-3-642-75935-2_8

Saaty, T. L. 1977. A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15(3): 234–281. https://doi.org/10.1016/0022-2496(77)90033-5

Saaty, T. L. 1999. Fundamentals of the analytic network process, in ISAHP 1999: International Symposium on the Analytic Hierarchy Process, 12–14 August 1999, Kobe, Japan, 34–45. https://doi.org/10.13033/isahp.y1999.038

Sarkar, A.; Panja, S. C.; Das, D.; Sarkar, B. 2015. Developing an efficient decision support system for non-traditional machine selection: an application of MOORA and MOOSRA, Production & Manufacturing Research 3(1): 324–342. https://doi.org/10.1080/21693277.2014.895688

Sehatpour, M.-H.; Kazemi, A.; Sehatpour, H.-E. 2017. Evaluation of alternative fuels for light-duty vehicles in Iran using a multi-criteria approach, Renewable and Sustainable Energy Reviews 72: 295–310. https://doi.org/10.1016/j.rser.2017.01.067

Shareef, H.; Islam, M. M.; Mohamed, A. 2016. A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles, Renewable and Sustainable Energy Reviews 64: 403–420. https://doi.org/10.1016/j.rser.2016.06.033

Shiau, T.-A.; Liu, J.-S. 2013. Developing an indicator system for local governments to evaluate transport sustainability strategies, Ecological Indicators 34: 361–371. https://doi.org/10.1016/j.ecolind.2013.06.001

Song, Z.; Li, J.; Hou, J.; Hofmann, H.; Ouyang, M.; Du, J. 2018. The battery-supercapacitor hybrid energy storage system in electric vehicle applications: a case study, Energy 154: 433–441. https://doi.org/10.1016/j.energy.2018.04.148

Stanković, M.; Gladović, P.; Popović, V. 2019. Determining the importance of the criteria of traffic accessibility using fuzzy AHP and rough AHP method, Decision Making: Applications in Management and Engineering 2(1): 86–104. https://doi.org/10.31181/dmame1901086s

Şimşek, A.; Çatır, O.; Ömürbek, N. 2015. TOPSIS ve MOORA yöntemleri ile tedarikçi seçimi: turizm sektöründe bir uygulama, Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 18(33): 133–161. https://doi.org/10.31795/baunsobed.645458 (in Turkish).

Vahdani, B.; Zandieh, M.; Tavakkoli-Moghaddam, R. 2011. Two novel FMCDM methods for alternative-fuel buses selection, Applied Mathematical Modelling 35(3): 1396–1412. https://doi.org/10.1016/j.apm.2010.09.018

Vaughan, M. L.; Faghri, A.; Li, M. 2018. Knowledge-based decision-making model for the management of transit system alternative fuel infrastructures, International Journal of Sustainable Development & World Ecology 25(2): 184–194. https://doi.org/10.1080/13504509.2017.1333541

Wang, B.; Song, J.; Ren, J.; Li, K.; Duan, H.; Wang, X. 2019a. Selecting sustainable energy conversion technologies for agricultural residues: a fuzzy AHP–VIKOR based prioritization from life cycle perspective, Resources, Conservation and Recycling 142: 78–87. https://doi.org/10.1016/j.resconrec.2018.11.011

Wang, H.; Jiang, Z.; Zhang, H.; Wang, Y.; Yang, Y.; Li, Y. 2019b. An integrated MCDM approach considering demands-matching for reverse logistics, Journal of Cleaner Production 208: 199–210. https://doi.org/10.1016/j.jclepro.2018.10.131

Wang, T.-C.; Chang, T.-H. 2007. Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications 33(4): 870–880. https://doi.org/10.1016/j.eswa.2006.07.003

Xu, Q.; Cai, T.; Liu, Y.; Yao, L.; Zheng, P. 2016. Location planning of charging stations for electric vehicles based on drivers’ behaviours and travel chain, Automation of Electric Power Systems 40(4): 59–65. https://doi.org/10.7500/AEPS20150704006 (in Chinese).

Yavuz, M.; Oztaysi, B.; Onar, S. Ç.; Kahraman, C. 2015. Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model, Expert Systems with Applications 42(5): 2835–2848. https://doi.org/10.1016/j.eswa.2014.11.010

Zhang, X.; Zhang, Q.; Sun, T.; Zou, Y.; Chen, H. 2018. Evaluation of urban public transport priority performance based on the improved TOPSIS method: a case study of Wuhan, Sustainable Cities and Society 43: 357–365. https://doi.org/10.1016/j.scs.2018.08.013

Zhang, Z.; Sun, X.; Ding, N.; Yang, J. 2019. Life cycle environmental assessment of charging infrastructure for electric vehicles in China, Journal of Cleaner Production 227: 932–941. https://doi.org/10.1016/j.jclepro.2019.04.167

Zubaryeva, A.; Thiel, C.; Barbone, E.; Mercier, A. 2012. Assessing factors for the identification of potential lead markets for electrified vehicles in Europe: expert opinion elicitation, Technological Forecasting and Social Change 79(9): 1622–1637. https://doi.org/10.1016/j.techfore.2012.06.004