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A novel integrated approach for strategic fleet planning in full-service carriers

Yıl 2026, Cilt: 16 Sayı: 1 , 330 - 351 , 26.03.2026

Murat Kartal , Buğra Bağcı

https://doi.org/10.30783/nevsosbilen.1827733
https://izlik.org/JA65PJ82YA

Öz

In the global air transportation sector, the growing demand for both passenger and cargo services has significantly increased the importance of strategic fleet planning. Wide-body aircraft play a crucial role in determining efficiency and service quality on long-haul routes. Selecting the right aircraft type is a critical decision-making process for airlines, impacting both operational effectiveness and economic sustainability. This study, proposes a decision model that integrates the IDOCRIW and MABAC methods for wide-body passenger aircraft selection in full-service carriers. Nine new-generation wide-body aircraft produced by Airbus and Boeing Companies are evaluated based on six criteria: cost, maximum seating capacity, fuel capacity, range, maximum take-off weight, and cargo capacity. Criterion weights are determined using the IDOCRIW method, and aircraft alternatives are ranked through the MABAC method. The analysis identifies the A350-1000 as the most suitable option, followed by the A350-900, B777-300ER and B777-200LR. The resulting ranking shows strong alignment with widely preferred aircraft models in the aviation industry. In addition to providing a practical model for decision-makers, this study also contributes to the limited literature on the integration of IDOCRIW and MABAC methodologies. This model not only assists in strategic aircraft selection, but also enables airline managers to make data-driven investment decisions, ensuring alignment with long-term operational priorities.

Anahtar Kelimeler

Airline fleet planning Full-service carriers Wide-body aircraft selection IDOCRIW method MABAC method

Kaynakça

  • Ahmed, S. K., Sivakumar, G., Kabir, G., & Ali, S. M. (2020). Regional aircraft selection integrating fuzzy analytic hierarchy process (FAHP) and efficacy method. Journal of Production Systems & Manufacturing Science, 1(2), 63-86.
  • Airbus. (2025). Aircraft specifications. Retrieved from https://www.airbus.com/en/products-services/commercial-aircraft/passenger-aircraft
  • Ardil, C. (2020). Aircraft selection process using preference analysis for reference ideal solution (PARIS). World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 14(3), 80-90.
  • Ardil, C. (2021). Comparison of composite programming and compromise programming for aircraft selection problem using multiple criteria decision making analysis method. World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 15(11), 479-485.
  • Ardil, C. (2022). Aircraft selection using preference optimization programming (POP). World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 16(11), 286–291.
  • Ardil, C. (2023). Aircraft selection process using reference linear combination in multiple criteria decision making analysis. World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 17(4), 146-155.
  • Bağcı, B. & Kartal, M. (2024). A combined multi criteria model for aircraft selection problem in airlines. Journal of Air Transport Management, 116, 102566. https://doi.org/10.1016/j.jairtraman.2024.102566
  • Bakır, M., Akan, Ş., & Özdemir, E. (2021). Regional aircraft selection with fuzzy PIPRECIA and fuzzy MARCOS: A case study of the Turkish airline industry. Facta Universitatis, Series: Mechanical Engineering, 19(3), 423-445. https://doi.org/10.22190/FUME210505053B
  • Belobaba, P., Odoni, A., & Barnhart, C. (2009). The global airline industry. Wiley.
  • Boeing. (2025). Commercial airplanes data. Retrieved from https://www.boeing.com/commercial/#/products-and-services
  • Bruno, G., Esposito, E., & Genovese, A. (2015). A model for aircraft evaluation to support strategic decisions. Expert Systems with Applications, 42(13), 5580-5590. https://doi.org/10.1016/j.eswa.2015.02.054
  • Cento, A. (2009). The Airline industry: challenges in the 21st century. Springer.
  • Çilek, A. (2023). Ranking the performance of market making banks: cilos, marcos and copeland multi-criteria decision making analysis, Pamukkale University Journal of Social Sciences Institute, 54, 1-24. https://doi.org/10.30794/pausbed.1092801
  • Dağlı, S. & Kuvvetli, B. İ. (2023). Performance evaluation of participation banks with different criteria weighting techniques and COCOSO method. Cukurova University Journal of the Faculty of Engineering, 38(4), 917-931. https://doi.org/10.21605/cukurovaumfd.1410252
  • Deveci, M., Öner, S. C., Ciftci, M. E., Özcan, E. & Pamucar, D. (2022). Interval type-2 hesitant fuzzy entropy-based WASPAS approach for aircraft type selection. Applied Soft Computing, 114, 108076. https://doi.org/10.1016/j.asoc.2021.108076
  • Deveci, M., Çiftçi, M. E., Isik, M., Pamucar, D., Wen, X., Chin, T., & Kadry, S. (2024). Aircraft type selection using fuzzy trigonometric based OPA and RAFSI model. Information Sciences, 673, 120688. https://doi.org/10.1016/j.ins.2024.120688
  • Dozic, S. & Kalic, M. (2014). An AHP approach to aircraft selection process. Transportation Research Procedia, 3, 165-174. https://doi.org/10.1016/j.trpro.2014.10.102
  • Dozic, S. & Kalic, M. (2015a). Comparison of two MCDM methodologies in aircraft type selection problem. Transportation Research Procedia, 10, 910-919. https://doi.org/10.1016/j.trpro.2015.09.044
  • Dozic, S. & Kalic, M. (2015b). Three-stage airline fleet planning model. Journal of Air Transport Management, 46, 30-39. https://doi.org/10.1016/j.jairtraman.2015.03.011
  • Dozic, S., Lutovac, T. & Kalic, M. (2018). Fuzzy AHP approach to passenger aircraft type selection. Journal of Air Transport Management, 68, 165-175. https://doi.org/10.1016/j.jairtraman.2017.08.003
  • Gomes, L. F. A. M., de Mattos Fernandes, J. E. & de Mello, J. C. C. S. (2012). A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. Journal of Advanced Transportation, 48(3), 223-237. https://doi.org/10.1002/atr.206
  • Güneş, H. G. (2022). Wide-body aircraft selection using multi-criteria decision making methods. [Master's thesis, Middle East Technical University].
  • Güntut, C. & Gökdalay, M. (2023). Aircraft selection decision support model for fleet planning of the low cost airlines. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 18(2), 460-478. https://doi.org/10.17153/oguiibf.1253980
  • Ilgın, M. A. (2019). Aircraft selection using linear physical programming. Journal of Aeronautics and Space Technologies, 12(2), 121-128.
  • Kaur, G., Dhara, A., Majumder, A., Sandhu, B. S., Puhan, A. & Adhikari, M. S. (2023). A CRITIC-TOPSIS MCDM technique under the neutrosophic environment with application on aircraft selection. Contemporary Mathematics, 1180-1203. https://doi.org/10.37256/cm.4420232963
  • Kiracı, K. & Bakır, M. (2018a). Using the multi criteria decision making methods in aircraft selection problems and an application. Journal of Transportation and Logistics, 3(1), 13-24. http://dx.doi.org/10.26650/JTL.2018.03.01.02
  • Kiracı, K. & Bakır, M. (2018b). Application of commercial aircraft selection in aviation industry through multi-criteria decision making methods. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 16(4), 307-332. https://doi.org/10.18026/cbayarsos.505987
  • Kiracı, K. & Akan, E. (2020). Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. Journal of Air Transport Management, 89, 1-16. https://doi.org/10.1016/j.jairtraman.2020.101924
  • Kocakaya, K., Engin, T., Tektaş, M. & Aydın, U. (2021). Aircraft selection for regional airlines in Turkey: an integration of spherical fuzzy AHP-TOPSIS methods. Akıllı Ulaşım Sistemleri ve Uygulama Dergisi, 4(1), 27-58. https://doi.org/10.51513/jitsa.903996
  • Macit, N. Ş. (2023). Evaluation of the macroeconomic performance of selected european and central asian countries by cilos based aroman method. Eurasian Academy of Sciences Eurasian Business & Economics Journal, 34, 31-48. https://doi.org/10.17740/eas.econ.2023-V34-03
  • Özdemir, Y., Basligil, H. & Karaca, M. (2011). Aircraft selection using analytic network process: a case for Turkish Airlines. Proceedings Of The World Congress On Engineering (WCE) Vol II, London, 9-13.
  • Pamučar, D. & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC). Expert systems with applications, 42(6), 3016-3028. https://doi.org/10.1016/j.eswa.2014.11.057
  • Podvezko, V., Kildienė, S. & Zavadskas, E. K. (2017). Assessing the performance of the construction sectors in the Baltic States and Poland. Panoeconomicus, 64(4), 493-512. https://doi.org/10.2298/PAN150518004P
  • Sarılgan, A. E. (2011). The requirements of developing the regional airline transportation in Turkey. Anadolu University Journal Of Social Sciences, 11(1), 69-88.
  • See, T. K., Gurnani, A. & Lewis, K. (2004). Multi-attribute decision making using hypothetical equivalents and inequivalents. J. Mech. Des., 126(6), 950-958.
  • Skytrax (2025). World airline awards 2024 rankings. Retrieved from https://www.worldairlineawards.com/worlds-top-10-airlines-2024/
  • Sun, X., Gollnick, V. & Stumpf, E. (2011). Robustness consideration in multi‐criteria decision making to an aircraft selection problem. Journal of Multi‐Criteria Decision Analysis, 18(1-2), 55-64. https://doi.org/10.1002/mcda.471
  • Şahin Macit, N. (2024). Quality of life in west asian countries: variables analyzed by idocriw-mara method and findings. Cumhuriyet University Journal of Economics and Administrative Sciences, 25(3), 467-487. https://doi.org/10.37880/cumuiibf.1460615
  • Yeh, C. H. & Chang, Y. H. (2009). Modeling subjective evaluation for fuzzy group multicriteria decision making. European Journal of Operational Research, 194(2), 464-473.
  • Zavadskas, E. K. & Podvezko, V. (2016). Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology & Decision Making, 15(02), 267-283. https://doi.org/10.1142/S0219622016500036
  • Zavadskas, E. K., Cavallaro, F., Podvezko, V., Ubarte, I. & Kaklauskas, A. (2017). MCDM assessment of a healthy and safe built environment according to sustainable development principles: a practical neighborhood approach in Vilnius. Sustainability, 9(5), 702. https://doi:10.3390/su9050702

Yıl 2026, Cilt: 16 Sayı: 1 , 330 - 351 , 26.03.2026

Murat Kartal , Buğra Bağcı

https://doi.org/10.30783/nevsosbilen.1827733
https://izlik.org/JA65PJ82YA

Öz

Kaynakça

  • Ahmed, S. K., Sivakumar, G., Kabir, G., & Ali, S. M. (2020). Regional aircraft selection integrating fuzzy analytic hierarchy process (FAHP) and efficacy method. Journal of Production Systems & Manufacturing Science, 1(2), 63-86.
  • Airbus. (2025). Aircraft specifications. Retrieved from https://www.airbus.com/en/products-services/commercial-aircraft/passenger-aircraft
  • Ardil, C. (2020). Aircraft selection process using preference analysis for reference ideal solution (PARIS). World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 14(3), 80-90.
  • Ardil, C. (2021). Comparison of composite programming and compromise programming for aircraft selection problem using multiple criteria decision making analysis method. World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 15(11), 479-485.
  • Ardil, C. (2022). Aircraft selection using preference optimization programming (POP). World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 16(11), 286–291.
  • Ardil, C. (2023). Aircraft selection process using reference linear combination in multiple criteria decision making analysis. World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 17(4), 146-155.
  • Bağcı, B. & Kartal, M. (2024). A combined multi criteria model for aircraft selection problem in airlines. Journal of Air Transport Management, 116, 102566. https://doi.org/10.1016/j.jairtraman.2024.102566
  • Bakır, M., Akan, Ş., & Özdemir, E. (2021). Regional aircraft selection with fuzzy PIPRECIA and fuzzy MARCOS: A case study of the Turkish airline industry. Facta Universitatis, Series: Mechanical Engineering, 19(3), 423-445. https://doi.org/10.22190/FUME210505053B
  • Belobaba, P., Odoni, A., & Barnhart, C. (2009). The global airline industry. Wiley.
  • Boeing. (2025). Commercial airplanes data. Retrieved from https://www.boeing.com/commercial/#/products-and-services
  • Bruno, G., Esposito, E., & Genovese, A. (2015). A model for aircraft evaluation to support strategic decisions. Expert Systems with Applications, 42(13), 5580-5590. https://doi.org/10.1016/j.eswa.2015.02.054
  • Cento, A. (2009). The Airline industry: challenges in the 21st century. Springer.
  • Çilek, A. (2023). Ranking the performance of market making banks: cilos, marcos and copeland multi-criteria decision making analysis, Pamukkale University Journal of Social Sciences Institute, 54, 1-24. https://doi.org/10.30794/pausbed.1092801
  • Dağlı, S. & Kuvvetli, B. İ. (2023). Performance evaluation of participation banks with different criteria weighting techniques and COCOSO method. Cukurova University Journal of the Faculty of Engineering, 38(4), 917-931. https://doi.org/10.21605/cukurovaumfd.1410252
  • Deveci, M., Öner, S. C., Ciftci, M. E., Özcan, E. & Pamucar, D. (2022). Interval type-2 hesitant fuzzy entropy-based WASPAS approach for aircraft type selection. Applied Soft Computing, 114, 108076. https://doi.org/10.1016/j.asoc.2021.108076
  • Deveci, M., Çiftçi, M. E., Isik, M., Pamucar, D., Wen, X., Chin, T., & Kadry, S. (2024). Aircraft type selection using fuzzy trigonometric based OPA and RAFSI model. Information Sciences, 673, 120688. https://doi.org/10.1016/j.ins.2024.120688
  • Dozic, S. & Kalic, M. (2014). An AHP approach to aircraft selection process. Transportation Research Procedia, 3, 165-174. https://doi.org/10.1016/j.trpro.2014.10.102
  • Dozic, S. & Kalic, M. (2015a). Comparison of two MCDM methodologies in aircraft type selection problem. Transportation Research Procedia, 10, 910-919. https://doi.org/10.1016/j.trpro.2015.09.044
  • Dozic, S. & Kalic, M. (2015b). Three-stage airline fleet planning model. Journal of Air Transport Management, 46, 30-39. https://doi.org/10.1016/j.jairtraman.2015.03.011
  • Dozic, S., Lutovac, T. & Kalic, M. (2018). Fuzzy AHP approach to passenger aircraft type selection. Journal of Air Transport Management, 68, 165-175. https://doi.org/10.1016/j.jairtraman.2017.08.003
  • Gomes, L. F. A. M., de Mattos Fernandes, J. E. & de Mello, J. C. C. S. (2012). A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. Journal of Advanced Transportation, 48(3), 223-237. https://doi.org/10.1002/atr.206
  • Güneş, H. G. (2022). Wide-body aircraft selection using multi-criteria decision making methods. [Master's thesis, Middle East Technical University].
  • Güntut, C. & Gökdalay, M. (2023). Aircraft selection decision support model for fleet planning of the low cost airlines. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 18(2), 460-478. https://doi.org/10.17153/oguiibf.1253980
  • Ilgın, M. A. (2019). Aircraft selection using linear physical programming. Journal of Aeronautics and Space Technologies, 12(2), 121-128.
  • Kaur, G., Dhara, A., Majumder, A., Sandhu, B. S., Puhan, A. & Adhikari, M. S. (2023). A CRITIC-TOPSIS MCDM technique under the neutrosophic environment with application on aircraft selection. Contemporary Mathematics, 1180-1203. https://doi.org/10.37256/cm.4420232963
  • Kiracı, K. & Bakır, M. (2018a). Using the multi criteria decision making methods in aircraft selection problems and an application. Journal of Transportation and Logistics, 3(1), 13-24. http://dx.doi.org/10.26650/JTL.2018.03.01.02
  • Kiracı, K. & Bakır, M. (2018b). Application of commercial aircraft selection in aviation industry through multi-criteria decision making methods. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 16(4), 307-332. https://doi.org/10.18026/cbayarsos.505987
  • Kiracı, K. & Akan, E. (2020). Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. Journal of Air Transport Management, 89, 1-16. https://doi.org/10.1016/j.jairtraman.2020.101924
  • Kocakaya, K., Engin, T., Tektaş, M. & Aydın, U. (2021). Aircraft selection for regional airlines in Turkey: an integration of spherical fuzzy AHP-TOPSIS methods. Akıllı Ulaşım Sistemleri ve Uygulama Dergisi, 4(1), 27-58. https://doi.org/10.51513/jitsa.903996
  • Macit, N. Ş. (2023). Evaluation of the macroeconomic performance of selected european and central asian countries by cilos based aroman method. Eurasian Academy of Sciences Eurasian Business & Economics Journal, 34, 31-48. https://doi.org/10.17740/eas.econ.2023-V34-03
  • Özdemir, Y., Basligil, H. & Karaca, M. (2011). Aircraft selection using analytic network process: a case for Turkish Airlines. Proceedings Of The World Congress On Engineering (WCE) Vol II, London, 9-13.
  • Pamučar, D. & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC). Expert systems with applications, 42(6), 3016-3028. https://doi.org/10.1016/j.eswa.2014.11.057
  • Podvezko, V., Kildienė, S. & Zavadskas, E. K. (2017). Assessing the performance of the construction sectors in the Baltic States and Poland. Panoeconomicus, 64(4), 493-512. https://doi.org/10.2298/PAN150518004P
  • Sarılgan, A. E. (2011). The requirements of developing the regional airline transportation in Turkey. Anadolu University Journal Of Social Sciences, 11(1), 69-88.
  • See, T. K., Gurnani, A. & Lewis, K. (2004). Multi-attribute decision making using hypothetical equivalents and inequivalents. J. Mech. Des., 126(6), 950-958.
  • Skytrax (2025). World airline awards 2024 rankings. Retrieved from https://www.worldairlineawards.com/worlds-top-10-airlines-2024/
  • Sun, X., Gollnick, V. & Stumpf, E. (2011). Robustness consideration in multi‐criteria decision making to an aircraft selection problem. Journal of Multi‐Criteria Decision Analysis, 18(1-2), 55-64. https://doi.org/10.1002/mcda.471
  • Şahin Macit, N. (2024). Quality of life in west asian countries: variables analyzed by idocriw-mara method and findings. Cumhuriyet University Journal of Economics and Administrative Sciences, 25(3), 467-487. https://doi.org/10.37880/cumuiibf.1460615
  • Yeh, C. H. & Chang, Y. H. (2009). Modeling subjective evaluation for fuzzy group multicriteria decision making. European Journal of Operational Research, 194(2), 464-473.
  • Zavadskas, E. K. & Podvezko, V. (2016). Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology & Decision Making, 15(02), 267-283. https://doi.org/10.1142/S0219622016500036
  • Zavadskas, E. K., Cavallaro, F., Podvezko, V., Ubarte, I. & Kaklauskas, A. (2017). MCDM assessment of a healthy and safe built environment according to sustainable development principles: a practical neighborhood approach in Vilnius. Sustainability, 9(5), 702. https://doi:10.3390/su9050702

Tam hizmet sağlayıcı havayolu işletmeleri için stratejik filo planlamasında yeni bir entegre yaklaşım

Yıl 2026, Cilt: 16 Sayı: 1 , 330 - 351 , 26.03.2026

Murat Kartal , Buğra Bağcı

https://doi.org/10.30783/nevsosbilen.1827733
https://izlik.org/JA65PJ82YA

Öz

Küresel hava taşımacılığı sektöründe, hızla artan yolcu ve kargo talebiyle birlikte stratejik filo planlamasının önemi her geçen gün artmaktadır. Özellikle geniş gövdeli uçaklar, uzun menzilli hatlarda verimlilik ve hizmet kalitesini doğrudan etkileyen unsurlar arasında yer almaktadır. Havayolu işletmeleri için doğru uçak tipinin belirlenmesi, hem operasyonel etkinlik hem de ekonomik sürdürülebilirlik açısından kritik bir karar süreci oluşturur. Bu çalışma, geleneksel (Tam Hizmet Sağlayıcı) havayolu işletmeleri için geniş gövde yolcu uçağı seçiminde çok kriterli karar verme yöntemlerinden IDOCRIW ve MABAC yaklaşımlarının birlikte kullanımını içeren bir karar modeli önermektedir. Airbus ve Boeing firmalarının ürettiği dokuz yeni nesil geniş gövde yolcu uçağı, satın alma maliyeti, yakıt kapasitesi, maksimum koltuk kapasitesi, menzil, maksimum kalkış ağırlığı ve kargo kapasitesi olmak üzere altı farklı kritere göre değerlendirilmiştir. Kriter ağırlıkları IDOCRIW yöntemi ile belirlenmiş; uçak alternatifleri ise MABAC yöntemiyle sıralanmıştır. Analiz sonucunda A350-1000 modeli en uygun seçenek olarak belirlenmiş; A350-900, B777-300ER ve B777-200LR modelleri ilk sıralarda yer almıştır. Elde edilen sıralama, havacılık sektöründe yaygın olarak tercih edilen uçaklarla yüksek oranda örtüşmektedir. Çalışma, karar vericilere pratik bir model sunmakla beraber, aynı zamanda IDOCRIW ve MABAC yöntemlerinin entegrasyonuna dayalı literatürdeki sınırlı çalışmalara önemli bir katkı sağlamaktadır.

Anahtar Kelimeler

Havayolu Filo Planlama Tam Hizmet Sağlayıcı Havayolları Geniş Gövde Uçak Seçimi IDOCRIW Yöntemi Mabac Yöntemi

Kaynakça

  • Ahmed, S. K., Sivakumar, G., Kabir, G., & Ali, S. M. (2020). Regional aircraft selection integrating fuzzy analytic hierarchy process (FAHP) and efficacy method. Journal of Production Systems & Manufacturing Science, 1(2), 63-86.
  • Airbus. (2025). Aircraft specifications. Retrieved from https://www.airbus.com/en/products-services/commercial-aircraft/passenger-aircraft
  • Ardil, C. (2020). Aircraft selection process using preference analysis for reference ideal solution (PARIS). World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 14(3), 80-90.
  • Ardil, C. (2021). Comparison of composite programming and compromise programming for aircraft selection problem using multiple criteria decision making analysis method. World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 15(11), 479-485.
  • Ardil, C. (2022). Aircraft selection using preference optimization programming (POP). World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 16(11), 286–291.
  • Ardil, C. (2023). Aircraft selection process using reference linear combination in multiple criteria decision making analysis. World Academy of Science, Engineering and Technology International Journal of Aerospace and Mechanical Engineering, 17(4), 146-155.
  • Bağcı, B. & Kartal, M. (2024). A combined multi criteria model for aircraft selection problem in airlines. Journal of Air Transport Management, 116, 102566. https://doi.org/10.1016/j.jairtraman.2024.102566
  • Bakır, M., Akan, Ş., & Özdemir, E. (2021). Regional aircraft selection with fuzzy PIPRECIA and fuzzy MARCOS: A case study of the Turkish airline industry. Facta Universitatis, Series: Mechanical Engineering, 19(3), 423-445. https://doi.org/10.22190/FUME210505053B
  • Belobaba, P., Odoni, A., & Barnhart, C. (2009). The global airline industry. Wiley.
  • Boeing. (2025). Commercial airplanes data. Retrieved from https://www.boeing.com/commercial/#/products-and-services
  • Bruno, G., Esposito, E., & Genovese, A. (2015). A model for aircraft evaluation to support strategic decisions. Expert Systems with Applications, 42(13), 5580-5590. https://doi.org/10.1016/j.eswa.2015.02.054
  • Cento, A. (2009). The Airline industry: challenges in the 21st century. Springer.
  • Çilek, A. (2023). Ranking the performance of market making banks: cilos, marcos and copeland multi-criteria decision making analysis, Pamukkale University Journal of Social Sciences Institute, 54, 1-24. https://doi.org/10.30794/pausbed.1092801
  • Dağlı, S. & Kuvvetli, B. İ. (2023). Performance evaluation of participation banks with different criteria weighting techniques and COCOSO method. Cukurova University Journal of the Faculty of Engineering, 38(4), 917-931. https://doi.org/10.21605/cukurovaumfd.1410252
  • Deveci, M., Öner, S. C., Ciftci, M. E., Özcan, E. & Pamucar, D. (2022). Interval type-2 hesitant fuzzy entropy-based WASPAS approach for aircraft type selection. Applied Soft Computing, 114, 108076. https://doi.org/10.1016/j.asoc.2021.108076
  • Deveci, M., Çiftçi, M. E., Isik, M., Pamucar, D., Wen, X., Chin, T., & Kadry, S. (2024). Aircraft type selection using fuzzy trigonometric based OPA and RAFSI model. Information Sciences, 673, 120688. https://doi.org/10.1016/j.ins.2024.120688
  • Dozic, S. & Kalic, M. (2014). An AHP approach to aircraft selection process. Transportation Research Procedia, 3, 165-174. https://doi.org/10.1016/j.trpro.2014.10.102
  • Dozic, S. & Kalic, M. (2015a). Comparison of two MCDM methodologies in aircraft type selection problem. Transportation Research Procedia, 10, 910-919. https://doi.org/10.1016/j.trpro.2015.09.044
  • Dozic, S. & Kalic, M. (2015b). Three-stage airline fleet planning model. Journal of Air Transport Management, 46, 30-39. https://doi.org/10.1016/j.jairtraman.2015.03.011
  • Dozic, S., Lutovac, T. & Kalic, M. (2018). Fuzzy AHP approach to passenger aircraft type selection. Journal of Air Transport Management, 68, 165-175. https://doi.org/10.1016/j.jairtraman.2017.08.003
  • Gomes, L. F. A. M., de Mattos Fernandes, J. E. & de Mello, J. C. C. S. (2012). A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. Journal of Advanced Transportation, 48(3), 223-237. https://doi.org/10.1002/atr.206
  • Güneş, H. G. (2022). Wide-body aircraft selection using multi-criteria decision making methods. [Master's thesis, Middle East Technical University].
  • Güntut, C. & Gökdalay, M. (2023). Aircraft selection decision support model for fleet planning of the low cost airlines. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 18(2), 460-478. https://doi.org/10.17153/oguiibf.1253980
  • Ilgın, M. A. (2019). Aircraft selection using linear physical programming. Journal of Aeronautics and Space Technologies, 12(2), 121-128.
  • Kaur, G., Dhara, A., Majumder, A., Sandhu, B. S., Puhan, A. & Adhikari, M. S. (2023). A CRITIC-TOPSIS MCDM technique under the neutrosophic environment with application on aircraft selection. Contemporary Mathematics, 1180-1203. https://doi.org/10.37256/cm.4420232963
  • Kiracı, K. & Bakır, M. (2018a). Using the multi criteria decision making methods in aircraft selection problems and an application. Journal of Transportation and Logistics, 3(1), 13-24. http://dx.doi.org/10.26650/JTL.2018.03.01.02
  • Kiracı, K. & Bakır, M. (2018b). Application of commercial aircraft selection in aviation industry through multi-criteria decision making methods. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 16(4), 307-332. https://doi.org/10.18026/cbayarsos.505987
  • Kiracı, K. & Akan, E. (2020). Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. Journal of Air Transport Management, 89, 1-16. https://doi.org/10.1016/j.jairtraman.2020.101924
  • Kocakaya, K., Engin, T., Tektaş, M. & Aydın, U. (2021). Aircraft selection for regional airlines in Turkey: an integration of spherical fuzzy AHP-TOPSIS methods. Akıllı Ulaşım Sistemleri ve Uygulama Dergisi, 4(1), 27-58. https://doi.org/10.51513/jitsa.903996
  • Macit, N. Ş. (2023). Evaluation of the macroeconomic performance of selected european and central asian countries by cilos based aroman method. Eurasian Academy of Sciences Eurasian Business & Economics Journal, 34, 31-48. https://doi.org/10.17740/eas.econ.2023-V34-03
  • Özdemir, Y., Basligil, H. & Karaca, M. (2011). Aircraft selection using analytic network process: a case for Turkish Airlines. Proceedings Of The World Congress On Engineering (WCE) Vol II, London, 9-13.
  • Pamučar, D. & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC). Expert systems with applications, 42(6), 3016-3028. https://doi.org/10.1016/j.eswa.2014.11.057
  • Podvezko, V., Kildienė, S. & Zavadskas, E. K. (2017). Assessing the performance of the construction sectors in the Baltic States and Poland. Panoeconomicus, 64(4), 493-512. https://doi.org/10.2298/PAN150518004P
  • Sarılgan, A. E. (2011). The requirements of developing the regional airline transportation in Turkey. Anadolu University Journal Of Social Sciences, 11(1), 69-88.
  • See, T. K., Gurnani, A. & Lewis, K. (2004). Multi-attribute decision making using hypothetical equivalents and inequivalents. J. Mech. Des., 126(6), 950-958.
  • Skytrax (2025). World airline awards 2024 rankings. Retrieved from https://www.worldairlineawards.com/worlds-top-10-airlines-2024/
  • Sun, X., Gollnick, V. & Stumpf, E. (2011). Robustness consideration in multi‐criteria decision making to an aircraft selection problem. Journal of Multi‐Criteria Decision Analysis, 18(1-2), 55-64. https://doi.org/10.1002/mcda.471
  • Şahin Macit, N. (2024). Quality of life in west asian countries: variables analyzed by idocriw-mara method and findings. Cumhuriyet University Journal of Economics and Administrative Sciences, 25(3), 467-487. https://doi.org/10.37880/cumuiibf.1460615
  • Yeh, C. H. & Chang, Y. H. (2009). Modeling subjective evaluation for fuzzy group multicriteria decision making. European Journal of Operational Research, 194(2), 464-473.
  • Zavadskas, E. K. & Podvezko, V. (2016). Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology & Decision Making, 15(02), 267-283. https://doi.org/10.1142/S0219622016500036
  • Zavadskas, E. K., Cavallaro, F., Podvezko, V., Ubarte, I. & Kaklauskas, A. (2017). MCDM assessment of a healthy and safe built environment according to sustainable development principles: a practical neighborhood approach in Vilnius. Sustainability, 9(5), 702. https://doi:10.3390/su9050702
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ekonometrik ve İstatistiksel Yöntemler
Bölüm Araştırma Makalesi
Yazarlar

Murat Kartal 0000-0002-0958-2655

Buğra Bağcı 0000-0002-3268-3702

Gönderilme Tarihi 21 Kasım 2025
Kabul Tarihi 31 Ocak 2026
Yayımlanma Tarihi 26 Mart 2026
DOI https://doi.org/10.30783/nevsosbilen.1827733
IZ https://izlik.org/JA65PJ82YA
Yayımlandığı Sayı Yıl 2026 Cilt: 16 Sayı: 1

Kaynak Göster

APA Kartal, M., & Bağcı, B. (2026). A novel integrated approach for strategic fleet planning in full-service carriers. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 16(1), 330-351. https://doi.org/10.30783/nevsosbilen.1827733