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DETERMINATION OF BEST MILITARY CARGO AIRCRAFT WITH MULTI- CRITERIA DECISION-MAKING TECHNIQUES

Year 2016, Volume: 5 Issue: 5, 87 - 101, 01.12.2016

Abstract

The changes that continually occur in the world’s economic, military, and diplomatic constraints and strategic targets lead countries to take preventive measures for their defense systems. One of these is that involving military cargo planes. The aim of this study is to determine the best options, by using multi-criteria decision-making approaches, for supplying military cargo aircraft, such as the AHP, SAW, ELECTRE and TOPSIS methods. Firstly, in this study, the military cargo aircraft are examined in order to determine if they meet the needs of and make a contribution to the Air Force in a deterrent capacity. Next, decision theory is studied and related subjects and definitions are explained. Later, all the methodologies are presented individually. All the criteria are defined during the application process. These criteria are operational effectiveness, the country’s share in the project, maintainability, maintenance easiness and cost-effectiveness. After this, a hierarchical model is composed and a comparison of criteria is made using the AHP and SAW methods; also the criteria of data related to the AHP method are used in the AHP, TOPSIS and ELECTRE methods. Finally, four different methods are used for three aircraft alternatives (A, B, C) and the best one ( C ) is determined

References

  • Afshari, A., Mojahed, M., & Yusuff, R. M. (2010). Simple additive weighting approach to personnel selection problem. International Journal of Innovation, Management and Technology,1, 511–515.
  • Gavade, R. K., (2010). Multi-Criteria Decision Making: An overview of different selection problems and methods. International Journal of Computer Science and Information Technologies, Vol. 5 (4), 5643-5646.
  • Gregory, G. (1988). In Decision analysis, Plenum Press, New York, 58-78.
  • Gurmeric, V. E., Dogan, M., Toker, Ö. S., Senyigit, E., Ersoz, N., B. (2013). Application of Different Multi- criteria Decision Techniques to Determine Optimum Flavour of Prebiotic Pudding Based on Sensory Analyses, Food Bioprocess Technol DOI 10.1007/s11947-012-0972-9, 6:2844–2859.
  • Gürbüz F., Yalçın N. (2013). A Swot- Fahp Application for A Textile Firm in Turkey. Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems, Papajorgji P., Guimarães A. M., Guarracino M. Eds., IGI GLOBAL, Pennsylvania , pp.45-57.
  • Jiang, J., Li, X., Zhou, Z., Xu, D., Chen, Y. (2011). Weapon System Capability Assessment under uncertainty based on the evidential reasoning approach, Expert Systems with Applications, Volume 38, 13773-1378.
  • Kamal, M., & Al-Harbi, A.-S. (2001). Application of the AHP in project management. International Journal of Project Management, 19, 19–27.
  • Korkmaz, İ., Gökçen, H., Çetinyokuş, T. (2008). An analytic hierarchy process and two-sided matching based decision support system for military personnel assignment, Information Sciences 178, 2915– 2927.
  • Pohekar, S. D., & Ramachandran, M. (2004). Application of multi-criteria decision making To sustainable energy planning—A review, Renewable and Sustainable Energy Reviews, 8, 365–381.
  • Saaty, T. L. (1980). The analytic hierarchy process. New-York: Mc-Graw Hill.
  • Sadeghzadeh, K., Salehi, M. B. (2011). Mathematical analysis of fuel cell strategic technologies development solutions in the automotive industry by the TOPSIS multi-criteria decision making method. International Journal of Hydrogen Energy, 36, 13272– 13280.
  • Schafer, J. (1979). Aircraft weight and balance, IAP Inc., Training Manual, Casper, Wyoming, USA.
  • Sherali, H. D. Staats, R. W., Trani, A. A. (2003). An Airspace Planning and Collaborative Decision-Making Model: Part I—Probabilistic Conflicts, Workload, and Equity Considerations, Transportation Science, Volume 37 Issue 4, pp. 434-456.
  • Sherali, H. D. Staats, R. W., Trani, A. A. (2006). An Airspace-Planning and Collaborative Decision-Making Model: Part II—Cost Model, Data Considerations, and Computations, Transportation Science, Volume 40 Issue 2, pp. 147-164.
  • Simanaviciene, R., Ustinovichius, L. (2010). Sensitivity Analysis for Multiple Criteria Decision Making Methods: TOPSIS and SAW, Procedia Social and Behavioral Sciences 2, 7743–7744.
  • Senyigit, E. and Golec, A. (2010). A new heuristic for multi-echelon defective supply chain system with stochastic demand, Proceedings of 7th International Symposium of Intelligent and Manufacturing System, 15-17.
  • Senyigit, E. (2012). The optimization of lot sizing with supplier selection problem in multi-echelon defective supply chain network. Mathematical and Computer Modelling of Dynamical Systems: Methods, Tools and Applications in Engineering and Related Sciences 18(3), 273-286.
  • Senyigit, E. and Soylemez, İ. (2012). The analysis of heuristics for lot sizing with supplier selection problem. Procedia - Social and Behavioral Sciences 62, 672–676.
  • Senyigit, E. (2013). Supplier selection and purchase problem for multi-echelon defective supply chain system with stochastic demand. Neural Computing and Applications, DOI: 10.1007/s00521-011-0704- 05, Volume 22, Issue 2, 403-415.
  • Triantaphyllou, E., Shu, B., Sanchez, S. N., Ray, T. (1998). Multicriteria decision making: An operations research approach. Encyclopedia of Electrical and Electronics Engineering, (J.G. Webster, Ed.), New York, Vol. 15, 175–186. D., http://naca.larc.nasa.gov/reports/1934/naca-report-447. of airplane propellers, NACA Report no. 447,
  • Yıldıztekin A., Şenyiğit E., Can A. (2011). The Location Selection of Freight Village In Samsun, IX. Internatıonal Logistics and Supply Chain Congress, vol.1, 7-16.

ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ

Year 2016, Volume: 5 Issue: 5, 87 - 101, 01.12.2016

Abstract

Dünya üzerinde değişen ekonomik, askeri, diplomatik kısıtlar ve stratejik hedefler, ülkelerin savunma sistemleri konusundaki ihtiyaçlarının ve bu ihtiyaç duyulan mal ve hizmetlerin de niteliklerinin artmasına sebep olmaktadır. Bu ihtiyaçların en önemlilerinden biri de askeri kargo uçaklarıdır. Silahlı birlikler içinde hem istenilen sayıda malzeme ve personel nakli yapabilen, hem içinde barındırdığı bütün uçak sistemleri açısından uçuş emniyetini en üst düzeyde tutabilen hem de harekât şartlarında bomba yüklenebilme, maksimum irtifaya çıkabilme, bir çıkışta azami süre havada kalabilme gibi harekât etkinliğini artıran faktörlere sahip olan en iyi alternatif uçağı belirlemek her ülke için önemli bir sorundur. Yukarıda belirtilen kriterlerin haricinde toplam maliyet etkinliği, idame edilebilirliği, hat ve depo seviyesi bakım kolaylıkları ile ülkelerin alım projeleri içindeki payları da, tercih edilecek alternatifte aranan temel başlıklardır. Bu çalışmanın amacı, ordularına askeri kargo uçağı katmak isteyen ülkelerin karar verici birimlerine, tespit edilen en önemli ve uygulanabilir kriterler ışığında, en uygun alternatifi bulmaları için çok kriterli karar verme tekniklerinden AHP, TOPSIS, ELEECTRE ve SAW metodlarının uygulanması suretiyle yol göstermektir

References

  • Afshari, A., Mojahed, M., & Yusuff, R. M. (2010). Simple additive weighting approach to personnel selection problem. International Journal of Innovation, Management and Technology,1, 511–515.
  • Gavade, R. K., (2010). Multi-Criteria Decision Making: An overview of different selection problems and methods. International Journal of Computer Science and Information Technologies, Vol. 5 (4), 5643-5646.
  • Gregory, G. (1988). In Decision analysis, Plenum Press, New York, 58-78.
  • Gurmeric, V. E., Dogan, M., Toker, Ö. S., Senyigit, E., Ersoz, N., B. (2013). Application of Different Multi- criteria Decision Techniques to Determine Optimum Flavour of Prebiotic Pudding Based on Sensory Analyses, Food Bioprocess Technol DOI 10.1007/s11947-012-0972-9, 6:2844–2859.
  • Gürbüz F., Yalçın N. (2013). A Swot- Fahp Application for A Textile Firm in Turkey. Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems, Papajorgji P., Guimarães A. M., Guarracino M. Eds., IGI GLOBAL, Pennsylvania , pp.45-57.
  • Jiang, J., Li, X., Zhou, Z., Xu, D., Chen, Y. (2011). Weapon System Capability Assessment under uncertainty based on the evidential reasoning approach, Expert Systems with Applications, Volume 38, 13773-1378.
  • Kamal, M., & Al-Harbi, A.-S. (2001). Application of the AHP in project management. International Journal of Project Management, 19, 19–27.
  • Korkmaz, İ., Gökçen, H., Çetinyokuş, T. (2008). An analytic hierarchy process and two-sided matching based decision support system for military personnel assignment, Information Sciences 178, 2915– 2927.
  • Pohekar, S. D., & Ramachandran, M. (2004). Application of multi-criteria decision making To sustainable energy planning—A review, Renewable and Sustainable Energy Reviews, 8, 365–381.
  • Saaty, T. L. (1980). The analytic hierarchy process. New-York: Mc-Graw Hill.
  • Sadeghzadeh, K., Salehi, M. B. (2011). Mathematical analysis of fuel cell strategic technologies development solutions in the automotive industry by the TOPSIS multi-criteria decision making method. International Journal of Hydrogen Energy, 36, 13272– 13280.
  • Schafer, J. (1979). Aircraft weight and balance, IAP Inc., Training Manual, Casper, Wyoming, USA.
  • Sherali, H. D. Staats, R. W., Trani, A. A. (2003). An Airspace Planning and Collaborative Decision-Making Model: Part I—Probabilistic Conflicts, Workload, and Equity Considerations, Transportation Science, Volume 37 Issue 4, pp. 434-456.
  • Sherali, H. D. Staats, R. W., Trani, A. A. (2006). An Airspace-Planning and Collaborative Decision-Making Model: Part II—Cost Model, Data Considerations, and Computations, Transportation Science, Volume 40 Issue 2, pp. 147-164.
  • Simanaviciene, R., Ustinovichius, L. (2010). Sensitivity Analysis for Multiple Criteria Decision Making Methods: TOPSIS and SAW, Procedia Social and Behavioral Sciences 2, 7743–7744.
  • Senyigit, E. and Golec, A. (2010). A new heuristic for multi-echelon defective supply chain system with stochastic demand, Proceedings of 7th International Symposium of Intelligent and Manufacturing System, 15-17.
  • Senyigit, E. (2012). The optimization of lot sizing with supplier selection problem in multi-echelon defective supply chain network. Mathematical and Computer Modelling of Dynamical Systems: Methods, Tools and Applications in Engineering and Related Sciences 18(3), 273-286.
  • Senyigit, E. and Soylemez, İ. (2012). The analysis of heuristics for lot sizing with supplier selection problem. Procedia - Social and Behavioral Sciences 62, 672–676.
  • Senyigit, E. (2013). Supplier selection and purchase problem for multi-echelon defective supply chain system with stochastic demand. Neural Computing and Applications, DOI: 10.1007/s00521-011-0704- 05, Volume 22, Issue 2, 403-415.
  • Triantaphyllou, E., Shu, B., Sanchez, S. N., Ray, T. (1998). Multicriteria decision making: An operations research approach. Encyclopedia of Electrical and Electronics Engineering, (J.G. Webster, Ed.), New York, Vol. 15, 175–186. D., http://naca.larc.nasa.gov/reports/1934/naca-report-447. of airplane propellers, NACA Report no. 447,
  • Yıldıztekin A., Şenyiğit E., Can A. (2011). The Location Selection of Freight Village In Samsun, IX. Internatıonal Logistics and Supply Chain Congress, vol.1, 7-16.
There are 21 citations in total.

Details

Other ID JA28JG38EC
Journal Section Research Article
Authors

Feyza Gurbuz This is me

Adem Göleç This is me

Ercan Şenyiğit This is me

Publication Date December 1, 2016
Submission Date December 1, 2016
Published in Issue Year 2016 Volume: 5 Issue: 5

Cite

APA Gurbuz, F., Göleç, A., & Şenyiğit, E. (2016). ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ. MANAS Sosyal Araştırmalar Dergisi, 5(5), 87-101.
AMA Gurbuz F, Göleç A, Şenyiğit E. ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ. MJSS. December 2016;5(5):87-101.
Chicago Gurbuz, Feyza, Adem Göleç, and Ercan Şenyiğit. “ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ”. MANAS Sosyal Araştırmalar Dergisi 5, no. 5 (December 2016): 87-101.
EndNote Gurbuz F, Göleç A, Şenyiğit E (December 1, 2016) ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ. MANAS Sosyal Araştırmalar Dergisi 5 5 87–101.
IEEE F. Gurbuz, A. Göleç, and E. Şenyiğit, “ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ”, MJSS, vol. 5, no. 5, pp. 87–101, 2016.
ISNAD Gurbuz, Feyza et al. “ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ”. MANAS Sosyal Araştırmalar Dergisi 5/5 (December 2016), 87-101.
JAMA Gurbuz F, Göleç A, Şenyiğit E. ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ. MJSS. 2016;5:87–101.
MLA Gurbuz, Feyza et al. “ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ”. MANAS Sosyal Araştırmalar Dergisi, vol. 5, no. 5, 2016, pp. 87-101.
Vancouver Gurbuz F, Göleç A, Şenyiğit E. ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE EN İYİ ASKERİ KARGO UÇAĞININ BELİRLENMESİ. MJSS. 2016;5(5):87-101.

MANAS Journal of Social Studies