Informatica logo


Login Register

  1. Home
  2. To appear
  3. Integration of Analytic Hierarchy Proces ...

Informatica

Information Submit your article For Referees Help ATTENTION!
  • Article info
  • Full article
  • Related articles
  • More
    Article info Full article Related articles

Integration of Analytic Hierarchy Process and Multi Attributive Border Approximation Area Comparison for the Hybrid Vehicle Selection Problem in Intuitionistic Fuzzy Environment
Esra Aytaç Adali ORCID icon link to view author Esra Aytaç Adali details   Ayşegül Tuş ORCID icon link to view author Ayşegül Tuş details  

Authors

 
Placeholder
https://doi.org/10.15388/25-INFOR596
Pub. online: 27 May 2025      Type: Research Article      Open accessOpen Access

Received
1 January 2025
Accepted
1 May 2025
Published
27 May 2025

Abstract

Nowadays sustainability and transportation concepts have been incorporated by the authorities and engineers. The indicator of this situation is the introduction of hybrid vehicles into the market. For the consumers, the purchasing process of hybrid vehicles is not easy because of the many alternatives with different brands including different properties. This process is considered a multi criteria problem with multi alternatives. This paper aims to develop a solution methodology for this problem of a company. The proposed methodology integrates the Interval Valued Intuitionistic Fuzzy (IVIF) sets and two Multi Criteria Decision Making (MCDM) methods; Analytic Hierarchy Process (AHP) and the Multi Attributive Border Approximation Area Comparison (MABAC). With the help of IVIF sets, the fuzziness in the structures of the decision problem and decision-making process is overcome. The IVIF AHP evaluation has revealed the importance that consumers attach to the criteria. According to the IVIF AHP results, each of the criteria has a similar weight. According to the IVIF MABAC results, the ranking order of the hybrid vehicle alternatives is specified as A1–A2–A3–A5–A4. The advantage of the integrated IVIF AHP and IVIF MABAC approach is that it helps in evaluating the most suitable alternatives when there is a disagreement about the relative suitability of the criteria and requires less numerical calculations. The results and the comparative analysis conducted in the study also support this situation.

References

 
Abdullah, L., Jaafar, J., Taib, I. (2009). A new analytic hierarchy process in multi-attribute group decision making. International Journal of Soft Computing, 4(5), 208–214.
 
Abdullah, L., Jaafar, S., Taib, I. (2013). Intuitionistic fuzzy analytic hierarchy process approach in ranking of human capital indicators. Journal of Applied Sciences, 13, 423–429.
 
Abdullah, L., Najib, L. (2014). A new preference scale of intuitionistic fuzzy analytic hierarchy process in multi-criteria decision making problems. Journal of Intelligent & Fuzzy Systems, 26(2), 1039–1049.
 
Abdullah, L., Najib, L. (2016). A new preference scale MCDM method based on interval-valued intuitionistic fuzzy sets and the analytic hierarchy process. Soft Computing, 20(2), 511–523.
 
Abdullah, L., Zulkifli, N., Liao, H., Herrera-Viedma, E., Al-Barakati, A. (2019). An interval-valued intuitionistic fuzzy DEMATEL method combined with Choquet integral for sustainable solid waste management. Engineering Applications of Artificial Intelligence, 82, 207–215.
 
Abdullah, L., Goh, C., Zamri, N., Othman, M. (2020). Application of interval valued intuitionistic fuzzy TOPSIS for flood management. Journal of Intelligent & Fuzzy Systems, 38(1), 873–881.
 
Acar, C., Haktanı, r.E., Temur, G.T., Beskese, A. (2024). Sustainable stationary hydrogen storage application selection with interval-valued intuitionistic fuzzy AHP. International Journal of Hydrogen Energy, 49, 619–634.
 
Ali, A., Ullah, K., Hussain, A. (2023). An approach to multi-attribute decision-making based on intuitionistic fuzzy soft information and Aczel-Alsina operational laws. Journal of Decision Analytics and Intelligent Computing, 3(1), 80–89.
 
Alkahtani, M., Al-Ahmari, A., Kaid, H., Sonboa, M. (2019). Comparison and evaluation of multi-criteria supplier selection approaches: A case study. Advances in Mechanical Engineering, 11(2), 1–19.
 
Arat, H.T. (2018). Numerical comparison of different electric motors (IM and PM) effects on a hybrid electric vehicle. Avrupa Bilim ve Teknoloji Dergisi, 14, 378–386.
 
Asif, M., Ishtiaq, U., Argyros, I.K. (2025). Hamacher aggregation operators for Pythagorean fuzzy set and its application in multi-attribute decision-making problem. Spectrum of Operational Research, 2(1), 27–40.
 
Atanassov, K. (1986). Intuitionistic fuzzy set. Fuzzy Sets Systems, 20, 87–96.
 
Atanassov, K., Gargov, G. (1989). Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 31, 343–349.
 
Aydın, S. (2021). Novel multi-expert MABAC method based on Fermatean fuzzy sets. Journal of Multiple-Valued Logic & Soft Computing, 37(5/6), 533–552.
 
Aytaç Adalı, A., Öztaş, T., Özçil, A., Öztaş, G.Z., Tuş, A. (2023). A new multi-criteria decision-making method under neutrosophic environment: ARAS method with single-valued neutrosophic numbers. International Journal of Information Technology & Decision Making, 22(01), 57–87.
 
Aytaç Adalı, A., Tuş, A. (2023). ARAS method based on Z-numbers in FMEA. Quality and Reliability Engineering International, 39(7), 3059–3081.
 
Ayyildiz, E. (2021). Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era. Environmental Science and Pollution Research, 30, 42476–42494.
 
Biswas, T.K., Das, M.C. (2018). Selection of hybrid vehicle for green environment using multi-attributive border approximation area comparison method. Management Science Letters, 8(2), 121–130.
 
Bošković, S., Švadlenka, L., Jovčić, S., Dobrodolac, M., Simić, V., Bačanin, N. (2023). An alternative ranking order method accounting for two-step normalization (AROMAN)–a case study of the electric vehicle selection problem. IEEE Access, 11, 39496–39507.
 
Bouraima, M.B., ldız E, A., Badi, I., Özçelik, G., Yeni, F.B., Pamucar, D. (2024). An integrated intelligent decision support framework for the development of photovoltaic solar power. Engineering Applications of Artificial Intelligence, 127, 107253.
 
Bureau of Transportation Statistics (2024). Gasoline, Hybrid and Electric Vehicle Sales. https://www.bts.gov/content/gasoline-hybrid-and-electric-vehicle-sales. Accessed 23 May 2025.
 
Büyüközkan, G., Feyzioğlu, O., Göçer, F. (2016). Evaluation of hospital web services using intuitionistic fuzzy AHP and intuitionistic fuzzy VIKOR. In: IEEE Int Conf Ind Eng Manag (Vol. 4–7), pp. 607–611.
 
Büyüközkan, G., Göçer, F. (2017). Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem. Applied Soft Computing, 52, 1222–1238.
 
Büyüközkan, G., Göçer, F., Feyzioğlu, O. (2018). Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods. Soft Computing, 22(15), 5091–5114.
 
Büyüközkan, G., Havle, C.A., Feyzioğlu, O. (2021a). Digital competency evaluation of low-cost airlines using an integrated IVIF AHP and IVIF VIKOR methodology. Journal of Air Transport Management, 91, 101998.
 
Büyüközkan, G., Mukul, E., Kongar, E. (2021b). Health tourism strategy selection via SWOT analysis and integrated hesitant fuzzy linguistic AHP-MABAC approach. Socio-Economic Planning Sciences, 74, 100929.
 
Cekerevac, Z. (2025). Ecological and economic risks of using gasoline, electric, hybrid, and hydrogen-powered vehicles. MEST Journal, 1–21.
 
Chen, T.Y., Wang, H.P., Lu, Y.Y. (2011). A multicriteria group decision-making approach based on interval-valued intuitionistic fuzzy sets: a comparative perspective. Expert Systems with Applications, 38(6), 7647–7658.
 
Chen, X., Fang, Y., Chai, J., Xu, Z. (2022). Does intuitionistic fuzzy analytic hierarchy process work better than analytic hierarchy process? International Journal of Fuzzy Systems, 24(2), 909–924.
 
Chowdhury, S.R., Chatterjee, S., Chakraborty, S. (2024). Optimization of grinding processes using multi-criteria decision making methods in intuitionistic fuzzy environment. OPSEARCH, 61, 709–740.
 
Deepika, M., Karthik Kannan, A.S. (2016). Global supplier selection using intuitionistic fuzzy analytic hierarchy process. In: Int Conf Electr, Electron, Optim Tech, 3–5 March, pp. 2390–2395.
 
Eti, S., Dinçer, H., Yüksel, S., Gökalp, Y. (2025). A new fuzzy decision-making model for enhancing electric vehicle charging infrastructure. Spectrum of Decision Making And Applications, 2(1), 94–99.
 
Fahmi, A., Derakhshan, A., Kahraman, C. (2015). August. Human resources management using interval valued intuitionistic fuzzy analytic hierarchy process. In: 2015 IEEE International Conference on Fuzzy Systems, 2–5 August, pp. 1–5.
 
Fan, Y., Xiao, F. (2020). TDIFS: Two dimensional intuitionistic fuzzy sets. Engineering Applications of Artificial Intelligence, 95, 103882.
 
Gitnux Editorial Team (2024). Hybrid Car Sales Statistics. https://blog.gitnux.com/hybrid-car-sales-statistics/. Accessed 23 May 2025.
 
Golui, S., Mahapatra, B.S., Mahapatra, G.S. (2024). A new correlation-based measure on Fermatean fuzzy applied on multi-criteria decision making for electric vehicle selection. Expert Systems with Applications, 237, 121605.
 
Gupta, P., Mehlawat, M.K., Grover, N., Pedrycz, W. (2018). Multi-attribute group decision making based on extended TOPSIS method under interval-valued intuitionistic fuzzy environment. Applied Soft Computing, 69, 554–567.
 
Gupta, P., Mehlawat, M.K., Grover, N. (2019). A generalized TOPSIS method for intuitionistic fuzzy multiple attribute group decision making considering different scenarios of attributes weight information. International Journal of Fuzzy Systems, 21(2), 369–387.
 
Haque, M.S., Sharif, S. (2021). The need for an effective environmental engineering education to meet the growing environmental pollution in Bangladesh. Cleaner Engineering and Technology, 4, 100114.
 
Hai, W., Qian, G., Xiangqian, F. (2011). An intuitionistic fuzzy AHP based on synthesis of eigenvectors and its application. Information Technology Journal, 10(10), 1850–1866.
 
Hashemkhani Zolfani, S., Görçün, Ö.F., Küçükönder, H. (2021). Evaluating logistics villages in Turkey using hybrid improved fuzzy SWARA (IMF SWARA) and fuzzy MABAC techniques. Technological and Economic Development of Economy, 27(6), 1582–1612.
 
Hezam, I.M., Mishra, A.R., Rani, P., Cavallaro, F., Saha, A., Ali, J., Strielkowski, W., Štreimikienė, D. (2022). A hybrid intuitionistic fuzzy-MEREC-RS-DNMA method for assessing the alternative fuel vehicles with sustainability perspectives. Sustainability, 14(9), 5463.
 
Hong, Y.H., Khan, N., Abdullah, M.M. (2013). The determinants of hybrid vehicle adoption: Malaysia perspective. Australian Journal of Basic and Applied Sciences, 7(8), 347–454.
 
Huo, J., Zhang, W., Chen, Z. (2024). Enhanced decision-making through an intelligent algorithmic approach for multiple-attribute college English teaching quality evaluation with interval-valued intuitionistic fuzzy sets. International Journal of Knowledge-based and Intelligent Engineering Systems, 28(2), 279–294.
 
Hu, S., Yang, J., Jiang, Z., Ma, M., Cai, W. (2021). CO2 emission and energy consumption from automobile industry in China: Decomposition and analyses of driving forces. Processes, 9(5), 810.
 
İç, Y.T., Şimşek, E. (2019). Operating window perspective integrated TOPSIS approach for hybrid electrical automobile selection. SN Applied Sciences, 1, 1314.
 
Ilbahar, E., Cebi, S., Kahraman, C. (2021a). Social acceptability assessment of renewable Energy Policies: An Integrated Approach Based on IVPF BOCR and IVIF AHP. In: International Conference on Intelligent and Fuzzy Systems. Springer, Cham, pp. 93–100.
 
Ilbahar, E., Cebi, S., Kahraman, C. (2021b). Risk assessment of R&D projects: a new approach based on IVIF AHP and fuzzy axiomatic design. Journal of Intelligent & Fuzzy Systems, 42(1), 605–614.
 
Jamkhaneh, E.B., Nadarajah, S. (2015). A new generalized intuitionistic fuzzy set. Hacettepe Journal of Mathematics and Statistics, 44(6), 1537–1551.
 
Jana, C., Garg, H., Pal, M., Sarkar, B., Wei, G. (2024). MABAC framework for logarithmic bipolar fuzzy multiple attribute group decision-making for supplier selection. Complex and Intelligent Systems, 10, 273–288.
 
Kahraman, C., Öztayşi, B., Onar, S. (2016). Intuitionistic fuzzy multicriteria evaluation of outsource manufacturers. IFAC-PapersOnLine, 49, 1844–1849.
 
Keshavarz-Ghorabaee, M., Amiri, M., Hashemi-Tabatabaei, M., Ghahremanloo, M. (2021). Sustainable public transportation evaluation using a novel hybrid method based on Fuzzy BWM and MABAC. The Open Transportation Journal, 15(1), 30–46.
 
Khan, F., Yousaf, A., Khan, A.U. (2020). Sustainable hybrid electric vehicle selection in the context of a developing country. Air Quality, Atmosphere, & Health, 13(4), 489–499.
 
Kirişci, M. (2024). Interval-valued Fermatean fuzzy based risk assessment for self-driving vehicles. Applied Soft Computing, 152, 111265.
 
Kumar, K., Kumar, S., Prajapati, D., Samir, S., Thapa, S., Kumar, R. (2025). Solar thermal collector roughened with S-shaped ribs: parametric optimization using AHP-MABAC technique. Fluids, 10(3), 67.
 
Kundakcı, N., Aytaç Adalı, E., Tuş, A. (2015). Tourist hotel location selection with analytic hierarchy process. Journal of Life Economics, 2(3), 47–58.
 
Li, D.F. (2011). Extension principles for interval-valued intuitionistic fuzzy sets and algebraic operations. Fuzzy Optimization and Decision Making, 10(1), 45–58.
 
Liu, H.C., You, J.X., Duan, C.Y. (2019). An integrated approach for failure mode and effect analysis under interval-valued intuitionistic fuzzy environment. International Journal of Production Economics, 207, 163–172.
 
Liu, P., Wang, D. (2021). A 2-dimensional uncertain linguistic MABAC method for multiattribute group decision-making problems. Complex & Intelligent Systems, 8, 349–360.
 
Liu, P., Zhang, P. (2021). A normal wiggly hesitant fuzzy MABAC method based on CCSD and prospect theory for multiple attribute decision making. International Journal of Intelligent Systems, 36(1), 447–477.
 
Lu, X., Lu, J., Yang, X., Chen, X. (2022). Assessment of urban mobility via a pressure-state-response (PSR) model with the IVIF-AHP and FCE methods: a case study of Beijing, China. Sustainability, 14(5), 3112.
 
Mandal, S., Gazi, K.H., Salahshour, S., Mondal, S.P., Bhattacharya, P., Saha, A.K. (2024). Application of interval valued intuitionistic fuzzy uncertain MCDM methodology for Ph.D supervisor selection problem. Results in Control and Optimization, 15, 100411.
 
Market Research Future (2025). Hybrid Vehicle Market Size, Trends, Growth and Forecast 2032. https://www.marketresearchfuture.com/reports/hybrid-vehicle-market-6025. Accessed 23 May 2025.
 
Mathew, M., Chakrabortty, R.K., Ryan, M.J., Ljaz, M.F., Khan, S.A.R. (2021). The multi-attributive border approximation area comparison (MABAC) method for decision making under interval-valued Fermatean fuzzy environment for green supplier selection. Preprints, 2021120209.
 
Mishra, A.R., Rani, P. (2018). Interval-valued intuitionistic fuzzy WASPAS method: application in reservoir flood control management policy. Group Decision and Negotiation, 27, 1047–1078.
 
Mishra, A.R., Chandel, A., Motwani, D. (2020). Extended MABAC method based on discrimination measures for multi-criteria assessment of programming language with interval-valued intuitionistic fuzzy sets. Granular Computing, 5(1), 97–117.
 
Moslem, S., Solieman, H., Oubahman, L., Duleba, S., Senapati, T., Pilla, F. (2023). Assessing public transport supply quality: a comparative analysis of analytical network process and analytical hierarchy process. Journal of Soft Computing and Decision Analytics, 1(1), 124–138.
 
Neizari, M.M., Nikandish, A., Samadi, B. (2017). A study on hybrid car purchasing intention. International Journal of Business and Social Sciences, 8(12), 46–56.
 
Onar, S.C., Oztaysi, B., Otay, I., Kahraman, C. (2015). Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets. Energy, 90, 274–285.
 
Ouyang, X., Guo, F. (2018). Intuitionistic fuzzy analytical hierarchical processes for selecting the paradigms of mangroves in municipal wastewater treatment. Chemosphere, 197, 634–642.
 
Pamučar, D., Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using multi attributive border approximation area comparison (MABAC). Expert System with Application, 42(6), 3016–3028.
 
Pamučar, D., Petrović, I., Ćirović, G. (2018). Modification of the Best-Worst and MABAC methods: a novel approach based on interval-valued fuzzy-rough numbers. Expert System with Application, 91, 89–106.
 
Patel, H., Chang, C.T. (2024). Beyond throughput: evaluating maritime port competitiveness using MABAC and Bayesian methods. Computers & Industrial Engineering, 110248.
 
Peng, X., Yang, Y. (2016). Pythagorean fuzzy Choquet integral based MABAC method for multiple attribute group decision making. International Journal of Intelligent Systems, 31, 989–1020.
 
Perçin, S. (2022). Circular supplier selection using interval-valued intuitionistic fuzzy sets. Environment, Development and Sustainability, 24(4), 5551–5581.
 
Pielecha, J., Skobiej, K., Kurtyka, K. (2020). Exhaust emissions and energy consumption analysis of conventional, hybrid, and electric vehicles in real driving cycles. Energies, 13(23), 6423.
 
Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., Pamučar, D. (2021). Application of interval fuzzy logic in selecting a sustainable supplier on the example of agricultural production. Symmetry, 13(5), 774.
 
Rani, P., Ali, J., Krishankumar, R., Mishra, A.R., Cavallaro, F., Ravichandran, K.S. (2021). An integrated single-valued neutrosophic combined compromise solution methodology for renewable energy resource selection problem. Energies, 14(15), 4594.
 
Roy, J., Ranjan, A., Debnath, A. (2016). An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers. https://arxiv.org/abs/1607.01254. Accessed July 29, 2019.
 
Roy, J., Chatterjee, K., Bandyopadhyay, A., Kar, S. (2017). Evaluation and selection of medical tourism sites: a rough AHP based MABAC approach. Expert Systems, 35(1), 1–19.
 
Saaty, T.L. (1980). The Analytic Hierarchy Process. McGraw-Hill, Newyork.
 
Saaty, R.W. (1987). The analytic hierarchy process-what it is and how it is used. Mathl Modelling, 9(3), 161–176.
 
Safaei Mohamadabadi, H., Tichkowsky, G., Kumar, A. (2009). Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles. Energy, 34, 112–125.
 
Sadiq, R., Tesfamariam, S. (2009). Environmental decision making under uncertainty using Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP). Stoch Environ Res Risk Assess, 23, 75–91.
 
Salman, M., Chauhan, R., Singh, T., Prabakaran, R., Kim, S.C. (2023). Experimental investigation and optimization of dimple-roughened impinging jet solar air collector using a novel AHP-MABAC approach. Environmental Science and Pollution Research, 30(13), 36259–36275.
 
Seker, S. (2020). Site selection for solar power plants using integrated two-stage hybrid method based on intuitionistic fuzzy AHP and COPRAS approach. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (Eds.), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. Springer, pp. 616–624.
 
Sharma, R.B., Maitra, B. (2024). Methodological approach to obtain key attributes affecting the adoption of plug-in hybrid electric vehicle. Case Studies on Transport Policy, 16, 101165.
 
Sundar Singh Sivam, S.P., Harshavardhana, N., Kumaran, D. (2024). Sustainable optimization through intuitionistic fuzzy MABAC of conical microcups fabrication in incremental sheet metal forming. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46(7), 445.
 
Sonar, H.C., Kulkarni, S.D. (2021). An integrated AHP-MABAC approach for electric vehicle selection. Research in Transportation Business & Management, 41(100665), 1–8.
 
Soon, W.L., Seng, W.T., Luen, W.K., Siang, J.M.L.D. (2013). Hybrid vehicle adoption – a conceptual study. Journal of Education and Vocational Research, 4(6), 165–168.
 
Sun, R., Hu, J., Zhou, J., Chen, X. (2018). A hesitant fuzzy linguistic projection-based MABAC method for patients’ prioritization. International Journal of Fuzzy Systems, 20, 2144–2160.
 
Suppes, G.J., Storvick, T.S. (2016). Sustainable Power Technologies and Infrastructure. 1st ed. Academic Press, London.
 
Tooranloo, H.S., Iranpour, A. (2017). Supplier selection and evaluation using interval-valued intuitionistic fuzzy AHP method. International Journal of Procurement Management, 10(105), 539–554.
 
Tran, M.K., Akinsanya, M., Panchal, S., Fraser, R., Fowler, M. (2021). Design of a hybrid electric vehicle powertrain for performance optimization considering various powertrain components and configurations. Vehicles, 3(1), 20–32.
 
Tumsekcali, E., Ayyildiz, E., Taskin, A. (2021). Interval valued intuitionistic fuzzy AHP-WASPAS based public transportation service quality evaluation by a new extension of SERVQUAL Model: P-SERVQUAL 4.0. Expert Systems with Applications, 186, 115757.
 
Tuğrul, F., Citil, M. (2022). Application of mathematical modeling in multi criteria decision making process: intuitionistic fuzzy PROMETHEE. Journal of Mathematical Sciences and Modelling, 5(2), 48–56.
 
Tuş, A., Aytaç Adalı, E. (2018). MABAC Method for an automobile selection problem. In: Proceedings of the VI. International Multidisciplinary Congress of Eurasia, (Rome), Italy, September 4–6, pp. 254–259.
 
Türkiye Statistical Institute (2025). Statistical Data Portal. https://data.tuik.gov.tr/. Accessed 23 May 2025.
 
Tütüncü, K.A., Gül, N.N., Bölükbaş, U., Güneri, A.F. (2023). Integer linear programming approach for the personnel shuttles routing problem in Yıldız Campus in İstanbul. Journal of Soft Computing and Decision Analytics, 1(1), 303–316.
 
Tzeng, G.H., Lin, C.W., Opricovic, S. (2005). Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy, 33, 1373–1383.
 
Ucarol, H., Kaypmaz, A., Tuncay, R.N., Tur, O. (2005). A performance comparison study among conventional, series hybrid and parallel hybrid vehicles. TUBITAK Marmara Research Center, Gebze, Kocaeli, Turkey. http://www.emo.org.tr/ekler/c792a8279211dec_ek.pdf.
 
Vahdani, B., Zandieh, M., Tavakkoli-Moghaddam, R. (2011). Two novel FMCDM methods for alternative-fuel buses selection. Applied Mathematical Modelling, 35, 1396–1412.
 
Verma, R. (2021). Fuzzy MABAC method based on new exponential fuzzy information measures. Soft Computing, 25, 9575–9589.
 
Wan, S., Dong, J. (2020). A possibility degree method for interval-valued intuitionistic fuzzy multi-attribute group decision making. Decision Making Theories and Methods Based on Interval-Valued Intuitionistic Fuzzy Sets, 1–35.
 
Wang, J., Wei, G., Wei, C., Wei, Y. (2020). MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment. Defence Technology, 16(1), 208–216.
 
Wang, G., Chen, C., Beshiwork, B.A., Lin, B. (2023a). Developing a low-carbon hybrid of ammonia fuel cell and internal combustion engine for carbon neutrality. Applications in Energy and Combustion Science, 16, 100214.
 
Wang, C., Yang, L., Zhang, X., Liang, R., Li, H., Wang, Y. (2023b). Optimisation analysis of distribution network planning based on the IVIF-AHP method. Applied Mathematics and Nonlinear Sciences, 8(2), 1105–1116.
 
Wang, J., Cai, Q., Wang, H., Wei, G., Liao, N. (2023c). An integrated decision-making methodology for green supplier selection based on the improved IVIF-CPT-MABAC method. Journal of Intelligent & Fuzzy Systems, 44(5), 8535–8560.
 
Wei, C.P., Wang, P., Zhang, Y.Z. (2011). Entropy, similarity measure of interval-valued intuitionistic fuzzy sets and their applications. Information Sciences, 181(19), 4273–4286.
 
Wu, J., Huang, H.B., Cao, Q.W. (2013). Research on AHP with interval-valued intuitionistic fuzzy sets and its application in multi-criteria decision making problems. Applied Mathematical Modelling, 37(24), 9898–9906.
 
Xu, Z., Chen, J. (2007). On geometric aggregation over interval-valued intuitionistic fuzzy information. In: Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 24–27 August, pp. 466–471.
 
Xu, Z.S. (2007). Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control and Decision, 22(2), 215–219.
 
Xu, Z.S., Chen, J. (2008). An overview of distance and similarity measures of intuitionistic fuzzy sets. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 16(4), 529–555.
 
Xu, Z., Liao, H. (2013). Intuitionistic fuzzy analytic hierarchy process. IEEE Transactions on Fuzzy Systems, 22(4), 749–761.
 
Xu, Z., Gou, X. (2017). An overview of interval-valued intuitionistic fuzzy information aggregations and applications. Granular Computing, 2(1), 13–39.
 
Xue, Y.X., You, J.X., Lai, X.D., Liu, H.C. (2016). An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Applied Soft Computing, 38, 703–713.
 
Yavuz, M., Oztaysi, B., Onar, S.C., Kahraman, C. (2015). Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model. Expert System with Application, 42, 2835–2848.
 
Yu, S.M., Wang, J., Wang, J.Q. (2017). An interval type-2 fuzzy likelihood-based MABAC approach and its application in selecting hotels on a tourism website. International Journal Fuzzy Systems, 19, 47–61.
 
Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
 
Zavadskas, E.K., Antucheviciene, J., Razavi Hajiagha, S.H., Hashemi, S.S. (2015). The interval-valued intuitionistic fuzzy MULTIMOORA method for group decision making in engineering. Mathematical Problems in Engineering, 2015(1), 1–13.
 
Zhang, S., Li, X., Meng, F. (2016). An approach to multicriteria decision-making under interval-valued intuitionistic fuzzy values and interval fuzzy measures. Journal of Industrial and Production Engineering, 33(4), 253–270.
 
Zhang, H., Wei, G., Chen, X. (2021). CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection. Journal of Intelligent & Fuzzy Systems, 41(1), 1009–1019.
 
Zhao, M., Wei, G., Chen, X., Wei, Y. (2021). Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making. International Journal of Intelligent Systems, 36(11), 6337–6359.
 
Zhu, J. (2013). Self-adaptation evaluation method in real time dynamics decision-making system based on grey close relationship. Grey Systems: Theory and Application, 3(3), 276–290.

Biographies

Aytaç Adali Esra
https://orcid.org/0000-0002-8836-9878
eaytac@pau.edu.tr

E. Aytaç Adalı is a professor at Pamukkale University in Denizli, Türkiye. She received her PhD from the Business Administration Department at Adnan Menderes University in Aydın, Türkiye. She has published over 40 publications in international/national journals/conferences. Her research interests are quality and quality control, fuzzy logic, and multi-criteria decision-making.

Tuş Ayşegül
https://orcid.org/0000-0003-1583-0616
atus@pau.edu.tr

A. Tuş is a professor at Pamukkale University in Denizli, Türkiye. She received her PhD from the Business Administration Department at Adnan Menderes University in Aydın, Türkiye. She has published over 45 publications in international/national journals/conferences. Her research interests are mathematical programming, fuzzy logic, and multi-criteria decision-making.


Full article Related articles PDF XML
Full article Related articles PDF XML

Copyright
© 2025 Vilnius University
by logo by logo
Open access article under the CC BY license.

Keywords
Interval Valued Intuitionistic Fuzzy sets Analytic Hierarchy Process Multi Attributive Border Approximation Area Comparison hybrid vehicle selection sustainability

Metrics
since January 2020
60

Article info
views

15

Full article
views

21

PDF
downloads

8

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
  • Copyright © 2023 Vilnius University

About

  • About journal

For contributors

  • OA Policy
  • Submit your article
  • Instructions for Referees
    •  

    •  

Contact us

  • Institute of Data Science and Digital Technologies
  • Vilnius University

    Akademijos St. 4

    08412 Vilnius, Lithuania

    Phone: (+370 5) 2109 338

    E-mail: informatica@mii.vu.lt

    https://informatica.vu.lt/journal/INFORMATICA
Powered by PubliMill  •  Privacy policy