Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2024 | 34 | 2 | 135-161

Article title

Evaluation and choice of an anti-aircraft missile system under uncertain conditions based on fuzzy-integral calculus and hierarchical cluster analysis

Content

Title variants

Languages of publication

EN

Abstracts

EN
Evaluation and choice of anti-aircraft missile weapon systems (AAMWSs) are a relevant problem in many countries. Estimates are often reduced to one top-level criterion. This is questionable since subordinated criteria are usually difficult to compare and decision-makers excluded from the final decision. The solution to the problem should also take into account non-statistical uncertainty. We propose to use a combination of two algorithms. The first algorithm calculates the estimates of AAMWSs in the criteria hierarchy using fuzzy-integral calculus. The hierarchy relates the characteristics of the AAMWSs to the three top-level criteria. In the space of these criteria, the second algorithm based on hierarchical clustering forms a class of the best AAMWSs equivalent to each other. The decision-maker makes the final choice from the obtained class, taking into account non-formalized factors. These algorithms are tested using the example of medium-range AAMWSs.

Year

Volume

34

Issue

2

Pages

135-161

Physical description

Contributors

  • Center for Military-Strategic Studies, National Defense University of Ukraine, Kiev, Ukraine
  • Center for Military-Strategic Studies, National Defense University of Ukraine, Kiev, Ukraine
author
  • Center for Military-Strategic Studies, National Defense University of Ukraine, Kiev, Ukraine

References

  • Akgun, İ., and Erdal, H. Solving an ammunition distribution network design problem using multi-objective mathematical modeling, combined AHP-TOPSIS, and GIS. Computers and Industrial Engineering 129 (2019), 512–528.
  • Albert, B. S. Cost-effectiveness evaluation for mixes of naval air weapons systems. Operations Research 11, 2 (1963), 173–189.
  • Allen, M. J., and Yen, W. M. Introduction to Measurement Theory. Waveland Press, 2001.
  • Ashari, H. E., and Parsaei, M. Application of the multi-criteria decision method ELECTRE III for the weapon selection. Decision Science Letters 3, 4 (2014), 511–522.
  • Bai, Y., and Wang, D. Evaluate and identify optimal weapon systems using fuzzy multiple criteria decision-making. In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011) (Taipei, Taiwan, 2011), IEEE, p. 1510–1515.
  • Béraud-Sudreau, L., Liang, X., Lopes da Silva, D., Tian N. and Scarazzato L. (December 2022) The SIPRI Top 100 Arms-Producing and Military Services Companies SIPRI Fact Sheet (accessed on 12 September 2023).
  • Bi, W., Gao, F., and Zhang, A. A novel weapon system effectiveness assessment method based on the interval-valuedevidential reasoning algorithm and the analytical hierarchy process. IEEE Access 9 (2021), 53480–53490.
  • Cernis, D., and Hasall, G. An innovative approach to weapon performance assessment. In Improving M&S Interoperability, Reuse and Efficiency in Support of Current and Future Forces. Meeting Proceedings NATO Modelling and Simulation Group RTOMP-MSG-056 (Neuilly-sur-Seine, France 2007), pp. 1–12.
  • Chameau, J.-L., and Santamarina, J. C. Membership functions I: Comparing methods of measurement. International Journal of Approximate Reasoning 1, 3 (1987), 287–301.
  • Chen, R.-S., and Shyu, J. Selecting a weapon system using zero-one goal programming and analytic network process. Journal of Information and Optimization Sciences 27, 2 (2006), 379–399.
  • Chen, S.-M. Evaluating weapon systems using fuzzy arithmetic operations. Fuzzy Sets and Systems 77, 3 (1996), 265–276.
  • Chen, S.-M. A new method for evaluating weapon systems using fuzzy set theory. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 26, 4 (1996), 493–497.
  • Cheng, C.-H. Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational Research 96, 2 (1997), 343–350.
  • Cheng, C.-H. Evaluating weapon systems using ranking fuzzy numbers. Fuzzy Sets and Systems 107, 1 (1999), 25–35.
  • Cheng, C.-H., and Lin, Y. Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research 142, 1 (2002), 174–186.
  • Cheng, C.-H., Liu, Y.-H., and Lin, Y. Evaluating a weapon system using catastrophe series based on fuzzy scales. In Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium (Kenting, Taiwan, 1996), IEEE, pp. 212–217.
  • Cheng, C.-H., and Mon, D.-L. Evaluating weapon system by analytical hierarchy process based on fuzzy scales. Fuzzy Sets and Systems 63, 1 (1994), 1–10.
  • Cheng, C.-H., and Mon, D.-L. Evaluating a weapon system using fuzzy analytical hierarchy process. Defence Science Journal 44, 2 (1994), 165–172.
  • Cho, H.-K., and Kim, W.-J. Development of evaluation index for foreign weapon system purchase using DEMATEL and AHP. Journal of the Korean Operations Research and Management Science Society 37, 2 (2012), 73–88.
  • Chu, T.-C., and Shih, W. An interval arithmetic method for evaluating weapon system under fuzzy environment. Journal of Information and Optimization Sciences 24, 2 (2003), 345–355.
  • Cline, R. E. A Survey and Summary of Mathematical and Simulation Models as Applied to Weapon System Evaluation. ASD Technical Report 61-276, Aeronautical Systems Division Air Force Systems Command, United States Air Force, 1961.
  • Dağdeviren, M., Yavuz, S., and Kılınç, N.Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications 36, 4 (2009), 8143–8151.
  • Dombi, J. Membership function as an evaluation. Fuzzy Sets and Systems 35, 1 (1990), 1–21.
  • Dos Santos, M., de Araujo Costa, I. P., and Gomes, C. F. S. Multicriteria decision-making in the selection of warships: a new approach to the AHP method. International Journal of the Analytic Hierarchy Process 13, 1 (2021), 147–169.
  • Erdal, H., Kurtay, K. G., Dagistanli, H. A., and Altundas, A. 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 (2023), 110145.
  • Eriskin, L., and Gunal, M. M. Test and evaluation for weapon systems: concepts and processes. In Operations Research for Military Organizations (Hershey, PA, USA 2019), H. Tozan and M. Karatas, Eds., IGI Global, pp. 98–110.
  • European Defence Agency (2022). Major defence exhibitions (accessed on 12 September 2023).
  • Galal, E. E. Criteria for evaluation of new weapon systems: Their future relevancy and effectiveness. In The Dangers of New Weapon Systems (London, 1983), W. Gutteridge and T. Taylor, Eds., Palgrave Macmillan, pp. 131–136.
  • Gao, F., Zhang, A., and Bi, W. Weapon system operational effectiveness evaluation based on the belief rule-based system with interval data. Journal of Intelligent and Fuzzy Systems 39, 5 (2020), 6687–6701.
  • Garmendia Salvador, L., Gonzalez del Campo, R., Lopez, V., and Recasens Ferres, J. An algorithm to compute the transitive closure, a transitive approximation and a transitive opening of a fuzzy proximity. Mathware and Soft Computing 16, 2 (2009), 175–191.
  • Greiner, M. A., Fowler, J. W., Shunk, D. L., Carlyle, W. M., and McNutt, R. T. A hybrid approach using the analytic hierarchy process and integer programming to screen weapon systems projects. IEEE Transactions on Engineering Management 50, 2 (2003), 192–203.
  • Han, Y., Liu, T. l., Li, Y., and Zhang, Z. j. Construction of intelligent weapon system effectiveness evaluation index system based on Delphi method. Journal of Physics: Conference Series 1570, (2020), 012049.
  • Harrington, E. C. The desirability function. Industrial Quality Control 21 (1965), 494–498.
  • Jabbarova, K. Multiattribute evaluation of weapon systems under Z-information. In 10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions - ICSCCW-2019 (Cham 2020), R. A. Aliev, J. Kacprzyk, W. Pedrycz, M. Jamshidi, M. B. Babanli and F. M. Sadikoglu, vol. 1095 of Advances in Intelligent Systems and Computing, Springer, pp. 359–365.
  • Jiang, J., Li, X., Zhou, Z.-J., Xu, D.-L., and Chen, Y.-W. Weapon system capability assessment under uncertainty based on the evidential reasoning approach. Expert Systems with Applications 38, 11 (2011), 13773–13784.
  • Kangaspunta, J., Liesiö, J., and Salo, A. Cost-efficiency analysis of weapon system portfolios. European Journal of Operational Research 223, 1 (2012), 264–275.
  • Karadayi, M. A., Ekinci, Y., and Tozan, H. A fuzzy MCDM framework for weapon systems selection. In Operations Research for Military Organizations. IGI Global, 2019, pp. 185–204.
  • Kim, D.-J., Lee, H.-W., Jung, J.-H., and Yong, H.-y. Usability evaluation criteria of software GUI on weapon system. Journal of the Korea Academia-Industrial cooperation Society 16, 12 (2015), 8691–8699.
  • Kim, H. W., Woo, S., and Jang, B. K. A study on readiness assessment for the acquisition of high quality weapon system. Journal of the Korean Society for Quality Management 41, 3 (2013), 395–404.
  • Kozakiewicz, A., and Wróblewski, M. Main problems of the evaluation and selection of advanced weapon systems exemplified by a multi-role combat aircraft. Biuletyn Wojskowej Akademii Technicznej 67, 3 (2018), 115–128.
  • Liao, S., Lu, K.-c., and Cheng, C.-h. Evaluating anti-armor weapon using ranking fuzzy numbers. Tamsui Oxford Journal of Mathematical Sciences 16, 2 (2000), 241–257.
  • Lide, S., Jianhua, H., and Jianqiang, W. Assessment for effectiveness of missile-gun integrated weapon system based on FSKA model. In 2011 International Conference on Electric Information and Control Engineering (Wuhan, 2011), IEEE, pp. 191–195.
  • Madhulatha, T. S. An overview on clustering methods, 2023. Working paper version available from arXiv: https://doi.org/10.48550/arXiv.1205.1117.
  • Li, J.-J., Liu L.-W. An MCDM model based on KL-AHP and TOPSIS and its application to weapon system evaluation. In Proceedings of the 5th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2014) (Paris, 2015), E. Qi, Q. Su, J. Shen, F. Wu, F. and R. Dou, Eds., vol. 1. Atlantis Press, pp. 257–262.
  • Maêda, S. M. d. N., Costa, I. P. d. A., Castro Junior, M. A. P. d., Fávero, L. P., Costa, A. P. d. A., Corricca, J. V. d. P., Gomes, C. F. S., and Santos, M. d. Multi-criteria analysis applied to aircraft selection by Brazilian Navy. Production 31, (2021), e20210011.
  • Magbagbeola, T. Assessing and Managing the Risk of Lethal Autonomous Weapons Systems. Master’s thesis, University of Stavanger, 2021.
  • Mon, D.-L., Cheng, C.-H., and Lin, J.-C. Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight. Fuzzy Sets and Systems 62, 2 (1994), 127–134.
  • Monnin, M., Iung, B., and Sónóchal, O. A methodology for weapon system availability assessment, incorporating failure, damage and regeneration. IFAC Proceedings Volumes 40, 6 (2007), 157–162.
  • Noghin, V. D. The Edgeworth-Pareto principle in terms of a fuzzy choice function. Computational Mathematics and Mathematical Physics 4 (2006), 554–562.
  • Othman, M., Khalid, S. A., Ismail, M., Rahman, N. A., and Yahaya, M. F. Fuzzy evaluation of weapons system. Computer and Information Science 2, 3 (2009), 24–31.
  • Pei, D., Qin, D., Sun, Y., Bu, G., and Yao, Z. Prioritization assessment for capability gaps in weapon system of systems based on the conditional evidential network. Applied Sciences 8, 2 (2018), 265.
  • Pospelov, D. A. Fuzzy Sets in Management and Artificial Intelligence Models. Nauka, 1986 (in Russian).
  • Robbe, C., Nsiampa, N., Papy, A., and Oukara, A. An hybrid experimental/numerical method to assess the lethality of a kinetic energy non-lethal weapon system (Freiburg, 2013). In 27th International Symposium on Ballistics, M. Wickert and M. Salk, Eds., DEStech Publications, pp. 482–494.
  • Saaty, T. L. Relative measurement and its generalization in decision-making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process. RACSAM-Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas 102, 2 (2008), 251–318.
  • Sánchez-Lozano, J. M., Correa-Rubio, J. C., and Fernández-Martínez, M. A double fuzzy multi-criteria analysis to evaluate international high-performance aircrafts for defense purposes. Engineering Applications of Artificial Intelligence 115 (2022), 105339.
  • Sánchez-Lozano, J. M., and Rodriguez, O. N. Application of fuzzy reference ideal method (FRIM) to the military advanced training aircraft selection. Applied Soft Computing 88 (2020), 106061.
  • Schwartz M. (23 May 2014). Defense acquisitions: How DoD acquires weapon systems and recent efforts to reform the process. Congressional Research Service (accessed on 12 September 2023).
  • Sugeno, M. Fuzzy measure and fuzzy integral. Transactions of the Society of Instrument and Control Engineers 8, 2 (1972), 218–226.
  • Sveshnikov, S., Bocharnikov, V., Pavlikovsky, A. and Prima, A. Estimating the potential willingness of the state to use military force based on the Sugeno fuzzy integral. Yugoslav Journal of Operations Research 32, 3 (2022), 325–356.
  • Tamura, S., Higuchi, S., and Tanaka, K. Pattern classification based on fuzzy relations. IEEE Transactions on Systems, Man, and Cybernetics SMC-1, 1 (1971), 61–66.
  • Wu, J., Dong, X., Fang, Q., Chen, Z., and Zeng, C. A novel effectiveness assessment method of weapon system based on triangular fuzzy number analytic hierarchy process. China Mechanical Engineering 24, 11 (2013) 1442-1446.
  • Wu, D., and Mendel, J. M. Computing with words for hierarchical decision-making applied to evaluating a weapon system. IEEE Transactions on Fuzzy Systems 18, 3 (2010), 441–460.
  • Yajie, D., Zhexuan, Z., Danling, Z., and Yong, W. Weapons system portfolio selection based on the contribution rate evaluation of system of systems. Journal of Systems Engineering and Electronics 30, 5 (2019), 905–919.
  • Yanto, I. T. R., Saedudin, R. R., Lashari, S. A., and Haviluddin. A numerical classification technique based on fuzzy soft set using hamming distance. In Recent Advances on Soft Computing and Data Mining: Proceedings of the Third International Conference on Soft Computing and Data Mining (SCDM 2018), Johor, Malaysia, February 06-07, 2018 (Cham 2018), R.Ghazali, M. M. Deris, N. M. Nawi and J. H. Abawajy, Eds., Springer, pp. 252–260.
  • Zhang, C., Ma, C., Liu, Z., and Xu, J. A new multi-attribute optimal selecting method for weapon system through trapezoidal fuzzy analytic hierarchy process and Delphi. In 2006 6th World Congress on Intelligent Control and Automation (Dalian, 2006), vol. 2, IEEE, pp. 7821–7825.
  • Zhang, S. T., Dou, Y. J., and Zhao, Q. S. Evaluation of capability of weapon system of systems based on multi-scenario. Advanced Materials Research 926-930 (2014), 3806–3811.
  • Zhao, Q., Ding, J., Li, J., and Hu, W. Mission-oriented scheme generation method for weapon system of systems. IEEE Access 8 (2020), 70981–70996.
  • Ziyuan, Q., Yangyang, Z., Liqing, F., Mengshan, J., Yanan, L., and Guoyu, L. Research on effectiveness evaluation method of weapon system based on cloud model. Journal of Physics: Conference Series 1965 (2021), 012005.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-0d00b0cf-58bb-4d68-814f-1772e750c732
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.