Journals / Savunma Bilimleri Dergisi / 2024 / Cilt: 20 Sayı: 2

Weapon Selection with Fuzzy AHP-TOPSIS for Capability-Based Risk-Based Defense Planning

Yetenek Temelli Risk Tabanlı Savunma Planlaması için Bulanık AHP-TOPSIS ile Silah Seçimi

Serkan Aksoy(MİLLİ SAVUNMA ÜNİVERSİTESİ, ALPARSLAN SAVUNMA BİLİMLERİ ENSTİTÜSÜ, SAVUNMA YÖNETİMİ ANABİLİM DALI, SAVUNMA TEDARİK VE LOJİSTİK YÖNETİMİ (YL) (TEZLİ))0009-0008-2006-1122
Memduh Begenirbaş(MİLLİ SAVUNMA ÜNİVERSİTESİ)0000-0003-0917-0973
Kemal Gürol Kurtay(MİLLİ SAVUNMA ÜNİVERSİTESİ, KARA HARP OKULU, ENDÜSTRİ VE SİSTEM MÜHENDİSLİĞİ BÖLÜMÜ)0000-0003-4268-2401
Pages
363–387
Publication Date
2024-11-01
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The main motivation of this study is to fill the gap in the literature regarding analytical evaluation of decision processes for identifying and evaluating scenario-based capabilities.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Capability-based planning (CAP) is a new paradigm that uses the concept of capability to provide an analytical framework for strategic or long-term planning.
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Key Findings & Data:In this study, 6 different scenarios were created for the capabilities that can meet military objectives, and accordingly, the risk of occurrence for each scenario was calculated within the YTP.
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Conclusion & Impact:The main motivation of this study is to fill the gap in the literature regarding analytical evaluation of decision processes for identifying and evaluating scenario-based capabilities.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Savunma planlaması · Yetenek temelli planlama · TOPSIS

Abstract

Capability-based planning (CAP) is a new paradigm that uses the concept of capability to provide an analytical framework for strategic or long-term planning. In this study, 6 different scenarios were created for the capabilities that can meet military objectives, and accordingly, the risk of occurrence for each scenario was calculated within the YTP. The sub-skills necessary for the success of the determined goals have been defined. For the weapon selection problem to meet military objectives, criterion weights were calculated with Fuzzy AHP, one of the Multi-Criteria Decision Making (MCDM) methods, and prioritized with the TOPSIS method. The main motivation of this study is to fill the gap in the literature regarding analytical evaluation of decision processes for identifying and evaluating scenario-based capabilities.

Özet

Yetenek temelli planlama (YTP), yeni bir paradigma olup stratejik veya uzun vadeli planlama için analitik bir çerçeve sunarak yetenek kavramını kullanmaktadır. Bu çalışmada askeri hedefleri sağlayabilecek yetenekler için 6 farklı senaryo oluşturulmuş ve buna göre YTP içerisinde her bir senaryo için meydana gelme riski hesabı yapılmıştır. Belirlenen hedeflerin başarılı olması için gerekli olan alt yetenekler tanımlanmıştır. Askeri hedeflerin karşılanmasına yönelik silah seçim problemi için Çok Kriterli Karar Verme (ÇKKV) yöntemlerinden Bulanık AHP ile kriter ağırlıkları hesaplanmış ve TOPSIS metodu ile önceliklendirilmesi yapılmıştır. Bu çalışmanın ana motivasyonu literatürdeki senaryo tabanlı yeteneklerin belirlenmesi ve değerlendirilmesi için karar süreçlerine ait analitik değerlendirmeye yönelik boşluğu doldurmaktır.

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Cite This Article

Aksoy, S., Begenirbaş, M., Kurtay, K. G. (2024). Weapon Selection with Fuzzy AHP-TOPSIS for Capability-Based Risk-Based Defense Planning. Savunma Bilimleri Dergisi, Cilt: 20 Sayı: 2, 363–387. https://doi.org/10.17134/khosbd.1494965

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References (53)

  1. Government, A. (2012). Defence capability development handbook 2012.
  2. Gaidow, S. ve Boey, S. (2005). Australian Defence Risk Management Framework: A Comparative Study.
  3. Barclay, C. ve Osei-Bryson, K. M. (2010). Project performance development framework: An approach for developing performance criteria & measures for information systems (IS) projects. International Journal of Production Economics, 124(1). https://doi.org/10.1016/j.ijpe.2009.11.025
  4. Martinsuo, M. (2013). Project portfolio management in practice and in context. International Journal of Project Management, 31(6). https://doi.org/10.1016/j.ijproman.2012.10.013
  5. Davis, P. K. (2002). Analytic architecture for capabilities-based planning, mission-system analysis, and transformation. Rand Corporation.
  6. Begenirbaş, M. (2022). Savunma yönetimi ve planlaması (1. Baskı). Nobel Akademik Yayıncılık.
  7. Stojkovic, D., Kankaras, M. ve Mitic, V. (2016). Determination of defence capability requirements. Vojno Delo, 68(8). https://doi.org/10.5937/vojdelo1608076s
  8. Mezey, G. (2004). Defence planning of conventional forces. 3(5).
  9. Campbell, A. (2010). Analytic implications of the NATO defence planning process. NATO C3 Agency.
  10. Cimon, Y. (2017). Perspectives for the development of key industrial capabilities for Canada’s defence sector. Defense and Security Analysis, 33(4). https://doi.org/10.1080/14751798.2017.1377422
  11. Palaz, H. (2008). Analitik hiyerarşi prosesi ve hedef programlama kullanılarak denizaltı kuvvet yapısının belirlenmesi (Yüksek Lisans Tezi). Hava Harp Okulu Komutanlığı Havacılık ve Uzay Teknolojileri Enstitüsü.
  12. Bizkevelci, S. ve Çakmak, M. A. (2008). Technology management model application in concept approval decision - Case study: Concept of operations and mission need assesment for a defence system. PICMET: Portland International Center for Management of Engineering and Technology, Proceedings.https://doi.org/10.1109/PICMET.2008.4599767
  13. Hristov, N., Radulov, I., Iliev, P. ve Andreeva, P. (2010). Prioritization methodology for development of required operational capabilities. Alındığı yer: https://ssrn.com/abstract=3135696
  14. Nesterenko, O., Netesin, I., Polischuk, V. ve Trofymchuk, O. (2020). Development of a procedure for expert estimation of capabilities in defense planning under multicriterial conditions. Eastern-European Journal of Enterprise Technologies, 4(2-106): 33-43. https://doi.org/10.15587/1729- 4061.2020.208603
  15. Harrison, K. R., Elsayed, S., Garanovich, I., Weir, T., Galister, M., Boswell, S., Taylor, R. ve Sarker, R. (2020). Portfolio optimization for defence applications. IEEE Access, 8: 60152- 60178. https://doi.org/10.1109/ACCESS.2020.2983141
  16. Kurtay, K. G., Dağıstanlı, H. A., & Erol, S. (2021). Plastik Boru ve Kaynak Makinesi Seçim Problemi için Analitik Hiyerarşi Prosesi ile Gri İlişkisel Analiz Yöntemlerinin Entegrasyonu. Savunma Bilimleri Dergisi, 2(40), 267-291. https://doi.org/10.17134/khosbd.1001230
  17. Desticioğlu, B., Kurtay, K. G., Altundaş, A., & Dağıstanlı, H. A. (2021). Hastanelere aşı dağıtımı için uygun rotaların belirlenmesi: Ankara ili örneği. Politeknik Dergisi, 26(1), 231- 241. https://doi.org/10.2339/politeknik.1014921
  18. Dagistanli, H. A., & Üstün, Ö. (2023). An integrated multi-criteria decision making and multi-choice conic goal programming approach for customer evaluation and manager assignment. Decision Analytics Journal, 8, 100270.https://doi.org/10.1016/j.dajour.2023.100270
  19. Altundaş, A., Kurtay, K. G., & Dağıstanlı, H. A. (2023). KBRN Kiti Dağıtım Ağı Tasarımı Optimizasyonu İçin Eş Zamanlı Topla Dağıt Araç Rotalama Problemi Yaklaşımı. SAVSAD Savunma ve Savaş Araştırmaları Dergisi, (1), 171-196.https://doi.org/10.54078/savsad.1370431
  20. Dağistanli, H. A. (2023). Çok ürünlü çok depolu araç rotalama problemi: askerî ilaç fabrikası örneği. Politeknik Dergisi, 1-1. https://doi.org/10.2339/politeknik.1224140
  21. Desticioğlu, B., & Ayan, M. A. (2022). Savunma Tedarik Konusunda Yapilan Çalişmalarin Bibliyometrik Analizi. SAVSAD Savunma ve Savaş Araştırmaları Dergisi, 32(1), 159-196. https://doi.org/10.54078/savsad.1134266
  22. Desticioglu Tasdemir, B., & Asilogullari Ayan, M. (2023, May). Sustainable Supplier Selection in the Defense Industry with Multicriteria Decision-Making Methods. In International Symposium on Intelligent Manufacturing and Service Systems (pp. 95-106). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-99-6062-0_10
  23. Taliaferro, L. M., Gonzalez, M., Tillman, P., Ghosh, P., Clarke, W., Hinkle, A. C. ve John Harvey, A. C. (2019a). Institute for defense analyses defense governance and Management: Improving the defense management capabilities of foreign defense institutions A Guide to Capability-Based Planning (CBP).
  24. Petras, Z. (2017). Comparative analysis of national approaches to military capability planning. International Conference KnowledgeBased Organization, 23(1). https://doi.org/10.1515/kbo-2017-0037
  25. Ciocan, F. (2011). Perspectives on interoperability integration within nato defense planning process. Journal of Defense Resources Management (JoDRM), 2(2).
  26. NATO. (2003). Handbook on long term defence planning work performed by the RTO Studies, Analysis and Simulation Panel (SAS). Distribution and Availability on Back Cover.
  27. Holcombe, S. G., Johnston, N. C., Candreva, P. ve Webb, N. J. (2008). Naval postgraduate school monterey, california mba professional report. Analysis of the PPBE Process in the Current Dynamic Political Environment.
  28. Church, A. T. W. (2009). DOD planning programming budgeting and execution system. JFQ Joint Force Quarterly, 53.
  29. Nelson, D. (2002). Beyond defense planning. Connections: The Quarterly Journal, 1(2). https://doi.org/10.11610/connections.01.2.08
  30. Drew, D. M. ve Snow, D. M. (2006). Making twenty-first-century strategy. An Introduction to Modern National Security Processes and Problems.
  31. Par Malan, L. (2019). The process of defence planning.
  32. Saraçoğlu, İ., & Dağıstanlı, H. A. (2017). Tedarikçi Seçiminde Bulanik Mantik-Ahp Ve Vikor Yönteminin Bağlanti Elemanlari Firmasinda Uygulanmasi. Yaşar Üniversitesi EDergisi, 12, 40-54.
  33. Kurtay, K. G., Gökmen, Y., Altundaş, A., & Dağıstanlı, H. A. (2021). Savunma Sanayii Projelerinin Çok Kriterli Karar Verme Yöntemleriyle Önceliklendirilmesi Ve Karşilaştirilmasi: Karma Bir Model Önerisi. Savsad Savunma ve Savaş Araştırmaları Dergisi, 31(1), 1-24.
  34. Erdal, H., Kurtay, K. G., Dagistanli, H. A., & Altundas, A. (2023). Evaluation of Anti-Tank Guided Missiles: An integrated Fuzzy Entropy and Fuzzy CoCoSo multi criteria methodology using technical and simulation data. Applied Soft Computing, 137, 110145. https://doi.org/10.1016/j.asoc.2023.110145
  35. Begenirbaş, M., Kurtay, K. G., Dağistanli, H. A., & Altundaş, A. (2023). Determining the Importance Level of Effective Criteria in the Employees in the Defense Acquisition Process via Fuzzy DEMATEL Method. Journal of Defense Sciences/Savunma Bilmleri Dergisi, 2(43). https://doi.org/10.17134/khosbd.1216154
  36. Erdal, H., Kurtay, K. G., & Dağıstanlı, H. A. (2024). Suggesting A Stochastic Measurement Tool for Determining Crime and Safety Indexes: Evidence from Turkey. Gazi University Journal of Science, 37(1), 339-355. https://doi.org/10.35378/gujs.1110735
  37. Dağıstanlı, H. A., & Kurtay, K. G. (2024). Facility Location Selection for Ammunition Depots based on GIS and Pythagorean Fuzzy WASPAS. Journal of Operations Intelligence, 2(1), 36-49. https://doi.org/10.31181/jopi2120247
  38. Dağıstanlı, H. A., & Gencer, C. Hibrit Tehdit Perspektifinden Orman Yangınları ve Türkiye’nin Mücadele Politikası. SAVSAD Savunma ve Savaş Araştırmaları Dergisi, (1), 35- 70. https://doi.org/10.54078/savsad.1377722
  39. Dupuy, T. N. (1979). Using history to evaluate combat factors and the outcome of battles. numbers. Predictions and War.
  40. Ciano, J. F. (1988). The Quantified Judgment Model and historic ground combat. Alındığı yer: http://hdl.handle.net/10945/23101
  41. Hogg, D. (1993). Correlation of forces: The quest for a standardized model. School of Advanced Military Studles United States Ary Command and General Staff College.
  42. Erkut, E. ve Ingolfsson, A. (2005). Transport risk models for hazardous materials: Revisited. Operations Research Letters, 33(1). https://doi.org/10.1016/j.orl.2004.02.006
  43. Aaron, C., Taliaferro, L. M., Gonzalez, M., Tillman, P., Ghosh, P., Clarke, W., Hinkle, A. C. ve John Harvey, A. C. (2019). Instıtute for defense analyses defense governance and management: Improving the defense management capabilities of foreign defense ınstitutions a guide to capability-based planning (CBP).
  44. Daǧdeviren, M., Yavuz, S. ve Kilinç, N. (2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications, 36(4). https://doi.org/10.1016/j.eswa.2008.10.016
  45. Lee, J., Kang, S. H., Rosenberger, J. ve Kim, S. B. (2010). A hybrid approach of goal programming for weapon systems selection. Computers and Industrial Engineering, 58(3). https://doi.org/10.1016/j.cie.2009.11.013
  46. Cheng, C. H. (1999). Evaluating weapon systems using ranking fuzzy numbers. Fuzzy Sets and Systems, 107(1). https://doi.org/10.1016/S0165-0114(97)00348-5
  47. Yu, Z., Tan, Y. J., Yang, K. W. ve Yang, Z. Y. (2012). Research on evolving capability requirements oriented weapon system of systems portfolio planning. Proceedings - 2012. 7th International Conference on System of Systems Engineering, SoSE 2012. https://doi.org/10.1109/SYSoSE.2012.6384128
  48. Zhang, S. T., Dou, Y. J. ve Zhao, Q. S. (2014). Evaluation of capability of weapon system of systems based on multi-scenario. Advanced Materials Research, 926-930. https://doi.org/10.4028/www.scientific.net/AMR.926-930.3806
  49. Kabak, M. (2011). Birlik hava savunma önceliklerinin tespitine bulanık bir yaklaşım. Savunma Bilimleri Dergisi, 10(2), 1-17.
  50. https://www.unroca.org/categories
  51. T.L. Saaty, A scaling method for priorities in hierarchical structures, J. Math. Psych. 15 (3) (1977) 234–281, http://dx.doi.org/10.1016/0022- 2496(77) 90033-5.
  52. C.L. Hwang, K. Yoon, C.L. Hwang, K. Yoon, Methods for multiple attribute decision making, in: Multiple Attribute Decision Making: Methods and Applications a State-of-the-Art Survey, 1981, pp. 58–191,
  53. Zhang, S. T., Dou, Y. J. ve Zhao, Q. S. (2014). Evaluation of capability of weapon system of systems based on multi-scenario. Advanced Materials Research, 926-930. https://doi.org/10.4028/www.scientific.net/AMR.926-930.3806