Evaluation of tanker vehicle selection using a novel hybrid fuzzy MCDM technique


  • Omer Faruk Gorcun Faculty of Business, Department of Business Management, Kadir Has University, Istanbul, Turkey
  • S. Senthil Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, India
  • Hande Küçükönder Department of Business Administration, Faculty of Economics and Administrative Sciences, Bartin University, Bartın, Turkey




Road Tanker Selection, Fuzzy SWARA, Fuzzy CODAS, dangerous goods transportation, MCDM


Petroleum product transportation considered as one of the crucial parts of dangerous material transportation is a risky logistics activity. The selection of the appropriate tanker vehicles may be a suitable solution to reduce the risks and increase the efficiency and performance of the fuel transportation companies. However, the selection of a suitable road tanker vehicle is not an easy task for decision-makers as there are many conflicting criteria and many decision alternatives. In addition, decision-makers may have to decide with insufficient information since collecting crisp values may not be possible at all times. Hence, many ambiguities affecting the evaluation results exist in an assessment process performed to select the best tanker vehicle option. This paper suggests a novel integrated fuzzy approach to solve these decision-making problems.  Sensitivity analysis is conducted to test the validation of the proposed integrated fuzzy approach and its results was performed by forming 130 scenarios. The results of sensitivity analysis prove that the proposed model can be applied to solve these kinds of decision-making problems.


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Ali, Z., Mahmood, T., Ullah, K., & Khan, Q. (2021). Einstein Geometric Aggregation Operators using a Novel Complex Interval-valued Pythagorean Fuzzy Setting with Application in Green Supplier Chain Management. Reports in Mechanical Engineering, 2(1), 105-134. https://doi.org/10.31181/rme2001020105t.

Alosta, A., Elmansuri, O., & Badi, I. (2021). Resolving a location selection problem by means of an integrated AHP-RAFSI approach. Reports in Mechanical Engineering, 2(1), 135-142. https://doi.org/10.31181/rme200102135a.

Bęczkowska, S. (2019). The method of optimal route selection in road transport of dangerous goods. Transportation Research Procedia, 40, 1252-1259.

Boral, S., Howard, I., Chaturvedi, S. K., McKee, K., & Naikan, V. N. A. (2020). An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA. Engineering Failure Analysis, 108, 104195.

Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1-9.

Dahooie, J. H., Vanaki, A. S. & Mohammadi, N. (2020). Choosing the appropriate system for cloud computing implementation by using the Interval-Valued Intuitionistic Fuzzy CODAS multiattribute decision-making method (Case Study: Faculty of New Sciences and Technologies of Tehran University)," in IEEE Transactions on Engineering Management, 67(3), 855-868.

Deveci, K., Cin, R. & Kağızman, A. (2020a). A modified interval valued intuitionistic fuzzy CODAS method and its application to multi-criteria selection among renewable energy alternatives in Turkey. Applied Soft Computing, 96, 106660.

Deveci, M., Özcan, E., John, R., Covrig, C.-F. & Pamucar, D. (2020b). A Study on Offshore Wind Farm Siting Criteria Using a Novel Interval-valued Fuzzy-rough based Delphi Method. Journal of Environmental Management, 270, 110916.

Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo'B) multicriteria model. Journal of Cleaner Production, 266, 121981.

Galieriková, A., Sosedová, J., Dávid, A. & Bariak, M. (2018). Transport of dangerous goods by rail. MATEC Web of Conferences, 2018, 235, 00004.

Görçün, Ö. F. (2019a). Ağır treylerlerin seçiminin AHP yöntemi ile değerlendirilmesi. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 7 (1), 383-398.

Görçün, Ö. F. (2019b). Karayolu yük taşımacılığında kullanılan standart treyler seçimine etki eden faktörlerin Analitik Hiyerarşi Prosesi ve TOPSIS yöntemleri ile değerlendirilmesi. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 7 (4), 23-34.

Gul, M., Guneri, A. F., & Nasirli, S. M. (2019). A fuzzy-based model for risk assessment of routes in oil transportation. International Journal of Environmental Science and Technology, 16, 4671-4686.

Hervás-Peralta, M., Poveda-Reyes, S., Santarremigia, F. E. Molero, G. D. (2020). Designing the layout of terminals with dangerous goods for safer and more secure ports and hinterlands. Case Studies on Transport Policy, 8(2), 300-310.

Huang, S. H. S., Hsu, W. K., Kevin, K., & Chen, J. W. (2020). A safety evaluation system based on a revised fuzzy AHP for dangerous goods in airfreights. Journal of Transportation Safety & Security, 12(5), 611-627.

Huang, W., Zhang, Y., Yu, Y., Xu, Y., Xu, M., Zhang, R., De Dieu, G. J., Yin, D. & Liu, Z. (2021). Historical data-driven risk assessment of railway dangerous goods transportation system: Comparisons between Entropy Weight Method and Scatter Degree Method. Reliability Engineering & System Safety, 205, 107236.

Jassbi, J. & Makvandi, P. (2010). Route selection based on soft MODM framework in transportation of hazardous materials. Applied Mathematical Sciences, 63(4), 3121-3132.

Jokić, Ž., Božanić, D., & Pamučar, D. (2021). Selection of fire position of mortar units using LBWA and Fuzzy MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 4(1), 115-135. https://doi.org/10.31181/oresta20401156j

Kanj H. & Abi-Char, P. E. (2019). A new Fuzzy-TOPSIS based risk decision making framework for dangerous good transportation. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), Zhangjiajie, China, 2019, 2666-2672.

Katranci, A., & Kundakci, N. (2020). Bulanık CODAS yöntemi ile kripto para yatirim alternatiflerinin değerlendirilmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 22(4), 958–973.

Keršuliene, V., Zavadskas, E. K. & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (Swara), Journal of Business Economics and Management, 11(2), 243-258, https://doi.org/10.3846/jbem.2010.12.

Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z. & Antucheviciene, J. (2016a). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation & Economic Cybernetics Studies & Research, 50(3), 25-44.

Keshavarz Ghorabaee, M., Zavadskas, E., Amiri, M., & Turskis, Z. (2016b). Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection. International Journal of Computers Communications & Control. 11. 358-371. 10.15837/ijccc.2016.3.2557.

Li, J. (2018). Multi-Objective Path Selection for Road Transportation of Dangerous Goods, 2018 IEEE 4th International Conference on Control Science and Systems Engineering (ICCSSE), 412-416, https://doi.org/doi: 10.1109/CCSSE.2018.8724681.

Mardani, A., Nilashi, M., Zakuan, N., Loganathan, N., Soheilirad, S., Saman, M.Z.M. & Ibrahim, O. (2017). A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments. Applied Soft Computing, 57, 265-292.

Mavi, R.K., Goh, M. & Zarbakhshnia, N. (2017). Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry. The International Journal of Advanced Manufacturing Technology, 91, 2401-2418.

Milosevic, T., Pamucar, D., Chatterjee, P. (2021). Model for selecting a route for the transport of hazardous materials using a fuzzy logic system. Military Technical Courier, 69(2), 355-390.

OECD. (2021). https://data.oecd.org/transport/passenger-car-registrations.htm Accessed 10 April 2021.

Ouhibi, A. & Frikha, H. M. (2020). Evaluating environmental quality in Tunisia using Fuzzy CODAS SORT method, 2020 International Conference on Decision Aid Sciences and Application (DASA), Sakheer, Bahrain, 1115-1119.

Pamucar, D. & Ecer, F. (2020). Prioritizing the weights of the evaluation criteria under fuzziness: The fuzzy full consistency method - FUCOM-F. Facta Universitatis, series: Mechanical Engineering. 18(3), 419-437.

Pamučar, D. & Janković, A. (2020). The application of the hybrid interval rough weighted Power-Heronian operator in multi-criteria decision making. Operational Research in Engineering Sciences: Theory and Applications, 3(2), 54-73.

Pamučar, D. Ljubojević, S. Kostadinović, D. & Đorović, B. (2016). Cost and risk aggregation in multi-objective route planning for hazardous materials transportation—a neuro-fuzzy and artificial bee colony approach. Expert Systems with Applications, 65, 1-15.

Pamučar, D., Sremac, S., Stević, Ž., Ćirović, G. & Tomić, D. (2019). New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods. Neural Computing and Applications, 31, 1-24.

Pamucar, D.S., & Savin, L.M. (2020). Multiple-criteria model for optimal off-road vehicle selection for passenger transportation: BWM-COPRAS model. Military Technical Courier, 68(1), 28-64.

Perçin, S. (2019). An integrated fuzzy SWARA and fuzzy AD approach for outsourcing provider selection. Journal of Manufacturing Technology Management, 30(2), 531–552.

Petrovic, G., Mihajlovic, J., Cojbasic, Z., Madic, M., & Marinkovic, D. (2019). Comparison of three fuzzy MCDM methods for solving the supplier selection problem. Facta Universitatis, Series: Mechanical Engineering, 17(3), 455-469.

Raemdonck, K. V., Macharis, C., & Mairesse, O. (2013). Risk analysis system for the transport of hazardous materials. Journal of Safety Research, 45, 55-63, https://doi.org/10.1016/j.jsr.2013.01.002.

Roy, J., Das, S., Kar, S. & Pamučar, D. (2019). An Extension of the CODAS approach using interval-valued intuitionistic fuzzy set for sustainable material selection in construction projects with incomplete weight information. Symmetry, 2019; 11(3), 393.

Samanlioglu, F. (2013). A multi-objective mathematical model for the industrial hazardous waste location-routing problem. European Journal of Operational Research, 226(2), 332-340.

Santarremigia, F. E., Molero, G. D., Poveda-Reyes, S. & Aguilar-Herrando, J. (2018), Railway safety by designing the layout of inland terminals with dangerous goods connected with the rail transport system. Safety Science, 110(Part B), 206-216.

Simic, V., Karagoz, S., Deveci, M. & Aydin, N. (2021). Picture fuzzy extension of the CODAS method for multi-criteria vehicle shredding facility location. Expert Systems with Applications, 175, 114644.

Stanković, M, Stević, Ž, Das, D.K., Subotić, M., & Pamučar, D. (2020). A New Fuzzy MARCOS Method for Road Traffic Risk Analysis. Mathematics, 8 (3), 457. https://doi.org/10.3390/math8030457.

Stanković, M., Stević, Ž., Das, D.K., Subotić, M. & Pamučar, D. (2020a). A new fuzzy MARCOS method for road traffic risk analysis. Mathematics, 2020; 8(3), 457.

Sumrit, D., Anuntavoranich, P. & Vadhanasindhu, P. (2012). Strategic decision for the external technological innovation acquisition mode selection by using an integration of AHP and GRA methods: a case study on a Thai new technology-based firm. IOSR Journal of Business and Management, 6(1), 29-38.

Vinodh, S., & Wankhede, V.A. (2020). Application of fuzzy DEMATEL and fuzzy CODAS for analysis of workforce attributes pertaining to Industry 4.0: a case study, International Journal of Quality & Reliability Management, https://doi.org/10.1108/IJQRM-09-2020-0322.

Wang, P., Wang, J., Wei, G., Wu, J., Wei, C. & Wei, Y. (2020). CODAS method for multiple attribute group decision making under 2-Tuple linguistic neutrosophic environment. Informatica, 31(1), 161-184.

Yalçın, N., & Pehlivan, N. (2019). Application of the Fuzzy CODAS Method Based on Fuzzy Envelopes for Hesitant Fuzzy Linguistic Term Sets: A Case Study on a Personnel Selection Problem. Symmetry, 11(4), 493, 1-27.

Yu, D.J., Wu, Y.Y. & Lu, T. (2012). Interval-valued intuitionistic fuzzy prioritized operators and their application in group decision making. Knowledge-Based Systems, 30, 57–66.

Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, 8(3), 338-353.

Zolfani, S.H. & Saparauskas, J. (2013). New application of SWARA method in prioritizing sustainability assessment indicators of energy system, Engineering Economics, 24(5), 408-414.



How to Cite

Gorcun, O. F., Senthil, S., & Küçükönder, H. (2021). Evaluation of tanker vehicle selection using a novel hybrid fuzzy MCDM technique. Decision Making: Applications in Management and Engineering, 4(2), 140–162. https://doi.org/10.31181/dmame210402140g