Optimization of a short-range surface-to-air artillery-missile system design process using the hybridized triangular IT2FS-DEMATEL-MABAC approach
Abstract
Introduction/purpose: The possibility of optimizing a short-range surface to air artillery-missile system (short-range SAAM) design process by applying hybridized multi-criteria decision-making (integration of DEMATEL and MABAC methods) approach in the triangular interval type 2 fuzzy environments is shown in the paper. By analyzing the content of the literature, the selection of the tactical-technical requirements and sub-requirements were determined. Furthermore, in the paper the weights of requirements and sub-requirements are determined. After that, a multi-criteria decision-making (MCDM) model was created for the evaluation of different initial projects of designing the short-range SAAM, which was also tested in this paper.
Methods: The proposed approach that combine DEMATEL and MABAC methods have been modified by triangular interval type 2 fuzzy sets (IT2FS). The triangular IT2F-DEMATEL method was applied to determine the requirements’ and sub-requirements’ weights, and the triangular IT2FS -MABAC method was applied to evaluate the alternatives – initial project designs of the short-range SAAM.
Results: Integrating multiple the triangular IT2FS-MCDM approach into a unique model that can be applied in the process of defining the optimal initial design project of the short-range SAAM.
Conclusion: The paper contributes to military science in making decisions related to the design of the short-range SAAM.
References
Baratimehr, K., Moosavi, M. R., & Tahayori, H. 2023. Measures for evaluating IT2FSs constructed from data intervals. Applied Soft Computing, 136, 110084.Available at: https://doi.org/10.1016/j.asoc.2023.110084
Baykasoğlu, A., & Gölcük, İ. 2017. Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS. Expert Systems with Applications, 70, pp. 37-51. Available at: https://doi.org/10.1016/j.eswa.2016.11.001.
Cheng, C. H. & Mon, D. L. 1994. Evaluating weapon system by analytical hierarchy process based on fuzzy scales. Fuzzy sets and systems, 63(1), pp. 1-10. Available at:https://doi.org/10.1016/0165-0114(94)90140-6.
Dağdeviren, M., Yavuz, S., & Kılınç, N. 2009. Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert systems with applications, 36(4), pp. 8143-8151. Available at: https://doi.org/10.1016/j.eswa.2008.10.016
Dağıstanlı, H. A. 2025. Weapon System Selection for Capability-Based Defense Planning using Lanchester Models integrated with Fuzzy MCDM in Computer Assisted Military Experiment. Knowledge and Decision Systems with Applications, 1, pp. 11-23. Available at: https://doi.org/10.59543/kadsa.v1i.13601
Demir, G. 2025. Strategic Assessment of IoT Technologies in Healthcare: Grey MCDM Approach. Spectrum of Decision Making and Applications, 2 (1), pp. 376-389. Available at: https://doi.org/10.31181/sdmap21202528
Deng, H., Sun, X., Liu, M., Ye, C., & Zhou, X. 2016. Image enhancement based on intuitionistic fuzzy sets theory. IET Image Processing, 10 (10), pp. 701-709. Available at: https://doi.org/10.1049/iet-ipr.2016.0035
Ding, J., Si, G., Ma, J., Wang, Y., & Wang, Z. 2018. Mission evaluation: expert evaluation system for large-scale combat tasks of the weapon system of systems. Science China Information Sciences, 61, pp. 1-19. Available at: https://doi.org/10.1007/s11432-016-9071-5
Field A. P. 2005. Kendall’s coefficient of concordance. In B Everitt and D Howell (Eds.), Encyclopedia of Statistics in Behavioral Science, pp 1010-1011. New York: Wiley. doi: 10.1002/0470013192. Availableat:https://discoveringstatistics.com/repository/kendall's_coefficient_of_concordance_ebs.pdf [Acessed: 23 March 2025].
Huang, H. D., Lee, C. S., Wang, M. H., & Kao, H. Y. 2014. IT2FS-based ontology with soft-computing mechanism for malware behavior analysis. Soft Computing, 18, pp. 267-284. Available at: https://doi.org/10.1007/s00500-013-1056-0
Jiang, J., Li, X., Zhou, Z. J., Xu, D. L., & Chen, Y. W. (2011). Weapon system capability assessment under uncertainty based on the evidential reasoning approach. Expert Systems with Applications, 38(11), 13773-13784. Available at: https://doi.org/10.1016/j.eswa.2011.04.179
Kahraman, C., Öztayşi, B., Sarı, İ. U., & Turanoğlu, E. 2014. Fuzzy analytic hierarchy process with interval type-2 fuzzy sets. Knowledge-Based Systems, 59, pp. 48-57. Available at: http://dx.doi.org/10.1016/j.knosys.2014.02.001.
Karadayi, M. A., Ekinci, Y., & Tozan, H. (2019). A Fuzzy MCDM Framework for Weapon Systems Selection. In Tozan H. & Karatas M. (Eds.) Operations Research for Military Organizations, pp. 185-204. IGI Global Scientific Publishing. Avaliable at: https://doi.org/10.4018/978-1-5225-5513-1.ch009
Kiracı, K., & Akan, E. 2020. Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. Journal of Air Transport Management, 89, pp. 1-16. Available at: https://doi.org/10.1016/j.jairtraman.2020.101924
Kolour, H. R., Momayezi, V., & Momayezi, F. 2025. Enhancing Supplier Selection in Public Manufacturing: A Hybrid Multi-Criteria Decision-Making Approach. Spectrum of Decision Making and Applications, 3 (1), pp. 1-20. Available at: https://doi.org/10.31181/sdmap31202629
Lee, H. S., Tzeng, G. H., Yeih, W., Wang, Y. J., & Yang, S. C. 2013. Revised DEMATEL: resolving the infeasibility of DEMATEL. Applied Mathematical Modelling, 37(10-11), pp. 6746-6757. Available at: https://doi.org/10.1016/j.apm.2013.01.016
Liu, Y., Yin, H., Xia, B., Yu, D., & Chen, Y. H. 2024. Interval type-2 fuzzy set-theoretic control design for uncertain dynamical systems. International Journal of Fuzzy Systems, 26(3), pp. 1069-1087. Available at: https://doi.org/10.1007/s40815-023-01654-3
Mavris, D., & DeLaurentis, D.1995. An integrated approach to military aircraft selection and concept evaluation. In:the 1st AIAA Aircraft Engineering Technology, and Operations Congress, Los Angeles, CA, pp.1-11. September 19-21.Available at: https://doi.org/10.2514/6.1995-3921
Mehdiabadi, A., Sadeghi, A., Yazdi, A. K., & Tan, Y. 2025. Sustainability service chain capabilities in the oil and gas industry: a fuzzy hybrid approach swara-mabac. Spectrum of Operational Research, 2 (1), pp. 92-112. Available at: https://doi.org/10.31181/sor21202512
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), pp. 3016-3028. Available at: https://doi.org/10.1016/j.eswa.2014.11.057
Petrović, I., & Milenković, M. 2024. Improvement of the operations planning process using a hybridized fuzzy-multi-criteria decision-making approach. Vojnotehnički glasnik/Military Technical Courier, 72(3), pp. 1093-1119. Available at: https://doi.org/10.5937/vojtehg72-51473
Petrović, M. & Petrović, I. 2024. Optimization of the design of combat systems on the example of a short - range artillery-missile air defense system using the IT2FS-DEMATEL method. In:SYM-OP-IS 2024: 51th International Symposium on Operational Research, Tara, pp.433-438. September16-19. 2024. Available at: https://symopis2024.ftn.uns.ac.rs/wp-content/uploads/2024/11/SYM-OP-IS-2024_PROCEEDINGS_final.pdf
Sabaei, D., Erkoyuncu, J. & Roy, R. 2015. A Review of Multi-criteria Decision Making Methods for Enhanced Maintenance Delivery. Procedia CIRP, 37, pp.30-35. Available at: https://doi.org/10.1016/j.procir.2015.08.086.
Shieh, J. I., & Wu, H. H. 2016. Measures of consistency for DEMATEL method. Communications in Statistics-Simulation and Computation, 45(3), pp. 781-790. Available at:https://doi.org/10.1080/03610918.2013.875564
Tešić, T. & Božanić, D. 2023. Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model. Acadlore Transactions on Applied Mathematics and Statistics, 1(3), pp.148-160. Available at: https://doi.org/10.56578/atams010303.
Uçal Sary, I., Öztayşi, B., & Kahraman, C. 2013. Fuzzy analytic hierarchy process using type‐2 fuzzy sets: An application to warehouse location selection. Multicriteria decision aid and artificial intelligence: Links, theory and applications, pp. 285-308.Available at: https://doi.org/10.1002/9781118522516.ch12
Yalçın, G. C., Kara, K., & Özyürek, H. 2025. Evaluating Financial Performance of Companies in the Borsa Istanbul Sustainability Index Using the CRITIC-MABAC Method. Spectrum of Operational Research, 2 (1), pp. 323-346. Available at: https://doi.org/10.31181/sor21202530
Zavadskas, E.K., Turskis, Z. & Kildienė, S. 2014. State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), pp.165-179. Available at: https://doi.org/10.3846/20294913.2014.892037
Copyright (c) 2025 Ivan Petrović, Милан Петровић

This work is licensed under a Creative Commons Attribution 4.0 International License.
Proposed Creative Commons Copyright Notices
Proposed Policy for Military Technical Courier (Journals That Offer Open Access)
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
