A hybrid fuzzy AHP-MABAC model: Application in the Serbian Army – The selection of the location for deep wading as a technique of crossing the river by tanks
In this paper is presented a hybrid model based on the fuzzified Analytical Hierarchical Process (AHP) method and the fuzzified Multi-Attributive Border Approximation Area Comparison (MABAC) method. The FAHP method is used for defining the weight coefficients of the criteria, while the FMABAC method is performed for the ranking of the alternatives. The fuzzification of the AHP method is carried out by defining a variable confidence interval for the values from the Saaty’s scale, which is derived from the comparison in pairs and the degree of certainty of the decision-makers in the comparison they make. The application of the hybrid model is shown on the example of the ranking of the locations for deep wading as a technique of crossing the river by the Serbian Army tank units. Through the paper are elaborated the criteria which condition such choice; also, the application of the method in a particular situation is demonstrated.
***(1971). Driving manual for tanks and armored vehicles (Only in Serbian: Priručnik za vožnju tenkova i oklopnih transportera). Belgrade: Federal Secretariat for National Defense, General Staff of the Yugoslav People's Army (JNA), Administration of armored units/SSNO, GŠ JNA, Uprava OJ.
***(1981). The military lexicon (Only in Serbian: Vojni leksikon). Belgrade: Military publishing institute/Vojnoizdavački zavod.
***(1984). Tank M-84, description, handling, basic and technical maintenance, Book 1 (Only in Serbian: Tenk M-84, opis, rukovanje, osnovno i tehničko održavanje, Knjiga 1.) Belgrade: Federal Secretariat for National Defense/SSNO, Technical book.
Abdullah, L., & Najib, L. (2014). A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process. Expert Systems with Applications, 41, 3297–3305.
Božanić, D., & Pamučar, D. (2016). Modification of the Saaty’s scale using a fuzzy number with a variable confidence interval: An example of a flood risk assessment (Only in Serbian: Modifikacija Saaty-jeve skale primenom fuzzy broja sa promenljivim intervalom poverenja: Primer procene opasnosti od poplava). In Savić, S., & Stanković, M. (Eds.), The Analytical Hierarchy Process - Theoretical foundations and applications in energy, protect the working environment and education (Only in Serbian: Analitički hijerarhijski proces - Teorijske osnove i primena u energetici, zaštiti radne i životne sredine i obrazovanju), Thematic collection (pp. 79-99), Niš: Research and development Center ALFATEC and Center for Complex Systems Research/Istraživačko-razvojni centar ALFATEC i Centar za istraživanje kompleksnih sistema.
Božanić, D., Karović, S., & Pamučar, D. (2015a). The fuzzification of Saaty’s scale using a triangular fuzzy number with a variable confidence interval (Only in Serbian: Fazifikacija Saaty-jeve skale primenom trouglastog fuzzy broja sa promenljivim intervalom poverenja). Proceedings of The Symposium on Operational Research (pp. 420-424). Srebrno jezero: The SANU Mathematical Institute.
Božanić, D., Pamučar, D., & Bojanić, D. (2015b). Modification of the Analytic Hierarchy Proces (AHP) Method using fuzzy logic: fuzzy AHP approach as a support to the decision making process concerning engagement of the Group for Additional Hindering. Serbian Journal of Management, 10(2), 151-171.
Božanić, D., Pamučar, D., & Đorović, B. (2013). Modification of Analytic Hierarchy Process (AHP) Method and its application in the Defense Decision-making. Tehnika, 68(2), 327-334.
Božanić, D., Pamučar, D., & Karović S. (2016b). Use of the fuzzy AHP – MABAC hybrid model in ranking potential locations for preparing laying-up positions. Vojnotehnički glasnik/Military Technical Courier, 64(3), 705-729.
Božanić, D., Pamučar, D., & Karović, S. (2016a). Application the MABAC method in support of decision-making on the use of force in a defensive operation. Tehnika, 71(1), 129-137.
Božanić, D., Pamučar, D., Đorović, B., Milić, A., & Lukovac V. (2011). Application of Fuzzy AHP Method on Selection of Actions Direction of the Group for Supplementary Obstacle Placing. Proceedings of The Symposium on Operational Research (pp. 556-559). Zlatibor: Faculty of Economics.
Božanić, D., Tešić, D., & Milićević, J. (2017). Selection of locations for Deep Draft Tank Crossing by applying fuzzy MABAC method. Proceedings of The 1st International Conference on Management, Engineering and Environment (ICMNEE) (pp. 346-358). Belgrade: ECOR (RABEK).
Bozbura, F.T., Beskese, A., & Kahraman, C. (2007). Prioritization of human capital measurement indicators using fuzzy AHP. Expert Systems with Applications, 32, 1100–1112.
Carnero, M.C. (2014). Multicriteria model for maintenance benchmarking. Journal of Manufacturing Systems, 33, 303–321.
Čupić, M., & Suknović, M. (2010). Decision making (Only in Serbian: Odlučivanje). Belgrade: Faculty of Organisational Sciences.
Deng Deng, Y., Xu, J., Liu, Y., & Mancl, K. (2014). Biogas as asustainable energy source in China: Regional development strategy application and decision making. Renewable and Sustainable Energy Reviews, 35, 294–303.
Devetak, S., & Terzić, M. (2011). Application of the analytic hierarchy process method in the selection of optimal tactical radio communication systems. Vojnotehnički glasnik/Military Technical Courier, 59(1), 161-176.
Gardašević-Filipović, M., & Šaletić, D. (2010). Multicriteria optimization in a fuzzy environment: the fuzzy Analytic hierarchy process. Yugoslav Journal of Operations Research, 20(1), 71-85.
Gordic, M., Slavkovic, R., & Talijan, M. (2013). A conceptual model of the state security system using the modal experiment. “Carol I” National Defence University Publishing House, 48(3), 58-67.
Isaai, M.T., Kanani, A., Tootoonchi, & M., Afzali, H.R. (2011). Intelligent timetable evaluation using fuzzy AHP. Expert Systems with Applications, 38, 3718–3723.
Janacković, G.L., Savić, S.M., & Stanković, M.S. (2013). Selection and ranking of occupational safety indicators based on fuzzy AHP: a case study in road construction companies. South African Journal of Industrial Engineering, 24 (3), 175-189.
Janjić, A., Stanković, M., & Velimorivć, L. (2014). Smart Grid Strategy Assessment Using the Fuzzy AHP. Proceedings of The Conference ICT FORUM (pp. 13-18), Niš: Regional Chamber of commerce.
John, A., Paraskevadakis, D., Bury, A., Yang, Z., & Riahi, R. (2014). An integrated fuzzy risk assessment for seaport operations. Safety Science, 68, 180–194.
Junior, F.R.L., Osiro, L., & Carpinetti, L.C.R. (2014). A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21, 194–209.
Kahraman, C., Öztayşi, B., Sari, I.U., & Turanoǧu, E. (2014). Fuzzy analytic hierarchy process with interval type-2 fuzzy sets. Knowledge-Based Systems, 59, 48–57.
Kamvysi, K., Gotzamani, K., & Andronikidis, A. (2014). Capturing and prioritizing students’ requirements for course designby embedding Fuzzy-AHP and linear programming in QFD. European Journal of Operational Research, 237, 1083–1094.
Kilic, H.S., Zaim, S., & Delen, D. (2014). Development of a hybrid methodology for ERP system selection:The case of Turkish Airlines. Decision Support Systems, 66, 82–92.
Li, L., Shi, Z.-H., Yin, W., Zhu, D., Ng, S.L., Cai, C.-F., & Lei, A-L. (2009). A fuzzy analytic hierarchy process (FAHP) approach to eco-environmental vulnerability assessment for the danjiangkou reservoir area, China. Ecological Modelling, 220, 3439–3447.
Martinović, G., & Simon, J. (2014). Greenhouse microclimatic environment controlled by a mobilemeasuring station. NJAS - Wageningen Journal of Life Sciences, 70–71, 61–70.
Meng, C., Xu, D., Son, Y.-J., Kubota, C., Lewis, M., & Tronstad, R. (2014). An integrated simulation and AHP approach to vegetable grafting operation design. Computers and Electronics in Agriculture, 102, 73–84
Milićević, M. (2014). Expert evaluation (Only in Serbian: Ekspertsko ocenjivanje).. Belgrade: Odbrana Media Center, Belgrade.
Miller, G. A. (1956). The magical number seven plus or minus two: some limits on our capacity for processing information. Psychological Review, 63, 81–97.
Mučibabić, S. (2003). Decision-making in conflict situations (Only in Serbian: Odlučivanje u konfliktnim situacijama). Belgrade: Military Academy.
Pamučar, D. (2011). Fuzzy-DEA model for measuring the efficiency of transport quality. Vojnotehnički glasnik/Military Technical Courier, 59(4), 40-61.
Pamučar, D., & Ćirović, D. (2015). The selection of transport and handling resources in logistics centres using Multi-Attributive Border Approximation area Comparison (MABAC). Expert systems with applications, 42(6), 3016-3028.
Pamučar, D., Božanić, D., & Đorović, B. (2011a). Fuzzy logic in decision making process in the Armed Forces of Serbia. Saarbrücken: LAMBERT Academic Publishing.
Pamučar, D., Božanić, D., & Kurtov, D. (2016). Fuzzification of the Saaty’s scale and a presentation of the hybrid fuzzy AHP-TOPSIS model: an example of the selection of a Brigade Artillery Group firing position in a defensive operation. Vojnotehnički glasnik/Military Technical Courier, 64(4), 966-986.
Pamučar, D., Ćirović, G., & Sekulović, D. (2015). Development of an integrated transport system in distribution centres: A FA’WOT analysi. Tehnički vjesnik, 22(3), 649-658.
Pamučar, D., Ćirović, G., Sekulović, D., & Ilić, A. (2011b). A new fuzzy mathematical model for multi criteria decision making: An application of fuzzy mathematical model in a SWOT analysis. Scientific Research and Essays, 6(25), 5374-5386.
Pamučar, D., Đorović, B, Božanic, D., & Ćirović, G. (2012). Modification of the dynamic scale of marks in analytic hierarchy process (ahp) and analytic network approach (anp) through application of fuzzy approach. Scientific Research and Essays, 7(1), 24-37.
Peng, X., & Yang, Y. (2016). Pythagorean Fuzzy Choquet Integral Based MABAC Method for Multiple Attribute Group Decision Making. International Journal of Intelligent Systems, 31, 989-1020.
Pifat, V. (1980). Crossing the river (Only in Serbian: Prelaz preko reka). Belgrade: Military publishing institute/Vojnoizdavački zavod.
Roy, J., Chatterjee, K., Bandhopadhyay, A., & Kar, S. (2017). Evaluation and selection of Medical Tourism sostes: A rough Analytic Hierarchy Process based Multi Attributive Border Approximation area Comparison approach. Expert Systems, e12232, https://doi.org/10.1111/exsy.12232.
Roy, J., Ranjan, A., Debnath, A., & Kar, S. (2016). An extended Multi Attributive Border Approximation area Comparison using interval type-2 trapezoidal fuzzy numbers. ArXiv ID: 1607.01254.
Saaty, T.L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
Seiford, L.M. (1996). The evolution of the state-of-art (1978-1995). Journal of Productivity Analysis, 7, 99-137.
Slavkovic, R., Talijan, M., & Jelic, M. (2012). Operatics in the system of defence sciences (military sciences). “Carol I” National Defence University Publishing House, 45(4), 88-100.
Slavkovic, R., Talijan, M., & Jelic, M. (2013). Relationship between theory and doctrine of operational art. Security and Defence Quarterly, 1(1), 54-75.
Srđević, B., Dantas, Y., & Modeiros, P. (2008). Fuzzy AHP Assessment of Water Management Plans. Water Resour Manage, 22, 877–894.
Teodorović, D., & Kikuchi, S. (1994). Fuzzy sets and applications in traffic and transport (Only in Serbian: Fuzzy skupovi i primene u saobraćaju i transportu). Belgrade: Faculty of Transport and Traffic Engineering.
Xue, Y.X., You, J.X., Lai, X.D., & Liu, H.C. (2016). An interval-valued intuitionistic fuzzy MABAC approach for materila selection with incomplete weight information. Applied Soft Computing, 38, 703-713.
Yu, S-m., Wang, J., & Wang, J-q. (2017). An Interval Type-2 Fuzzy Likelihood-Based MABAC Approach and Its Aplication in Selecting Hotels on a Tourism Website. International Journal of Fuzzy Systems, 19(1), 47-61.