Fuzzy Delphi approach to defining a cycle for assessing the performance of military drivers

Vesko Lukovac; Milena Popović

doi:10.31181/dmame180167l

Authors

Vesko Lukovac University of defence in Belgrade, Military academy, Department of logistics, Belgrade, Serbia
Milena Popović University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia

DOI:

https://doi.org/10.31181/dmame180167l

Keywords:

Fuzzy Delphi Approach, Cycle, Evaluating Performance, Military Drivers

Abstract

This paper presents the Fuzzy Delphi approach to defining a cycle for assessing the performance of military drivers. This approach is based on the Delphi decision-making process under uncertainty. These uncertainties are described by linguistic terms modeled with triangular fuzzy numbers. The approach is modeled to take into the account the importance - weight of each decision-maker and the homogeneity of their individual fuzzy preferences. The vertex method calculates the distance between the aggregated Fuzzy estimation and the triangular fuzzy numbers in which the linguistic terms which experts had chosen are modeled. Defuzzification of the fuzzy preference of the experts was carried out by a Graded Mean Integration Representation.

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References

Bogićević Milikić, B. (2008). Human Resource Management, Faculty of Economics Belgrade.

Chang, P. L., Hsu, C. W., & Chang, P. C. (2011). Fuzzy Delphi method for evaluating hydrogen production technologies. International journal of hydrogen energy, 36(21), 14172-14179.

Chen, M. F., & Tzeng, G. H. (2004). Combining grey relation and TOPSIS concepts for selecting and expatriate host country. Mathematical and Computer Modeling, 40 (13), 1473-1490.

Cheng, C. H., & Lin, Y. (2002). Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European journal of operational research, 142(1), 174-186.

Dubois, D., & Prade, H. (1980). Fuzzy Sets and Systems: Theory and Applications, London, UK: Academic press, INC (London) LTD.

Gigović, L., Pamučar, D., Lukić, D., & Marković, S. (2016). GIS-Fuzzy DEMATEL MCDA model for the evaluation of the sites for ecotourism development: A case study of “Dunavski ključ” region, Serbia. Land use policy, 58, 348-365.

Grout, D. (2008). Performance Evaluation and Improvement: Questions and Answers, Manager's Handbook, ASEE, Novi Sad.

Ishikawa, A., Amagasa, M., Shinga, T., Tomizawa, G., Tatsuta, R., & Mieno, H. (1993). The max-min Delphi method and fuzzy Delphi method via fuzzy integration.Fuzzy Sets and systems, 55 (3), 241-253.

Jovanović, M., Kulić, Ž., & Cvetkovski, T. (2004). Human Resource Management, Megatrend University, Belgrade.

Kashdan, B. T. (2004). The assessment of subjective well-being (issues raised by the Oxford Happiness Questionnaire).Personality and Individual Differences,36 (5), 1225-1232.

Klir, G. J., & Yuan, B. (1995). Fuzzy Sets and Fuzzy Logic, Theory and Applications, New Jersy, Prentice Hall, USA.

Lukovac V., Pamučar D., & Jovanović V. (2012). Assessor distributional errors in evoluating employees’ work quality – identification and decrase, Proceedings of XIII International Symposium SYMORG 2012, Zlatibor.

Lukovac V., Pejčić-Tarle S., Popović M., &Pamučar D. (2014). Distribution errors in the employee performance evaluation process, Military Technical Courier, 62 (4), 141-154.

Lukovac, V. (2010). A model for evaluating the quality of military drivers, magister thesis, Faculty of Transport and Traffic Engineering, Belgrade.

Lukovac, V. (2016). A model for evaluating the quality of military drivers, dissertation, University of Defense in Belgrade, Military Academy, Belgrade.

Lukovac, V., & Popović, M. (2017). Fuzzy Delphi approach to defining the start and the end of a cycle for assessing the performance of military drivers, The 1st International Conference on Management, Engineering and Environment, ICMNEE 2017, Belgrade, September 28-29, 198-209.

Noe, A. R., Hollenbeck, R. J., Gerhart, B., & Wright, M. P. (2006). Human Resource Management, third Edition, MATE d.o.o, Zagreb.

Pamučar, D., Ćirović, G., Sekulović, D., & Ilić, A. (2011). 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.

Saaty, T.L. (1980). The analytic hierarchy process, McGraw-Hill, New York.

Tadić, D., Pravdić, P., Arsovski. Z., Arsovski, S., & Aleksić, A. (2013). Ranking and managing business goals of manufacturing organizations by Balanced scorecard under uncertainties. Technics Technologies Education Management, 8 (3), 13-28.

Vujić, D. (2008). Human resource management and quality, Faculty of Philosophy, Belgrade.

Wu, K. Y. (2011). Applying the Fuzzy Delphi Method to Analyze the Evaluation Indexes for Service Quality after Railway Re-Opening-Using the Old Mountain Line Railway as an Example, Proceedings of the 15th WSEAS international conference on Systems, World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA.

Young, S. J., & Jamieson, L. M. (2001). Delivery methodology of the Delphi: A comparison of two approaches. Journal of Park and Recreation Administration, 19 (1), 42-58.

Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.