Expert System of Two-Stages in Simulated Environment for Selection of Staff
November 30, 2017
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This article is an original work that presents an Expert System (ES) in fuzzy logic, to attend to the problem of selection of staff in a Persian Lime exporting company in Veracruz-Mexico. The ES is constructed considering a Recruitment stage, and a second Selection stage which is characterized in particular by being simulated in the vacancy functions called and including in that stage a TOPSIS module that helps to qualify complementary traits of the candidate. The use of the ES proves to be an effective support tool for the making decision, eliminates the vagueness of judges, and decreases administrative time in meetings for such activity. The criteria of selection of staff codified in the ES makes its use applicable not only to the exporting companies of this citrus, but can be extended to any other company.
Lavoignet-Ruíz, M., Fernández-Lambert, G., Peralta-Rodríguez, J. E., Aguilar-Lasserre, A., & Guendulay-Escalante, G. (2017). Expert System of Two-Stages in Simulated Environment for Selection of Staff. RA Journal Of Applied Research, 3(11), 1217–1226. Retrieved from http://rajournals.in/index.php/rajar/article/view/127
1. Afshari, A., Yusuff, R., & Derayatifar, A. (2013). Linguistic Extension of Fuzzy Integral for Group Personnel Selection Problem. Arabian Journal for Science & Engineering (Springer Science & Business Media BV), 38(10). doi:10.1007/s13369-012-0491-z
2. Afshari, R. A., Nikolić, M., & Ćoćkalo, D. (2014). Applications of fuzzy decision making for personnel selection problem: A review. Journal of Engineering Management and Competitiveness (JEMC), 4(2), 68-77.
3. Aggarwal, R. (2014). Identifying and Prioritizing Human Capital Measurement Indicators for Personnel Selection Using Fuzzy MADM. In Proceedings of the Third International Conference on Soft Computing for Problem Solving (pp. 427-439). Springer, New Delhi. doi:10.1007/978-81-322-1771-8_37
4. Aguilar Lasserre, A. A., Lafarja Solabac, M. V., Hernandez-Torres, R., Posada-Gomez, R., Juárez-Martínez, U., & Fernández Lambert, G. (2014). Expert system for competences evaluation 360 feedback using fuzzy logic. Mathematical Problems in Engineering, 2014. doi:10.1155/2014/789234
5. Akhlagh, E. (2011). A rough-set based approach to design an expert system for personnel selection. World Academy of Science, Engineering and Technology, 54, 202 205.
6. Aksakal, E., & Dagdeviren, M. (2010). An Integrated Approach for Personel Selection with DEMATEL and ANP Methods. Journal of The Faculty of Engineering and Architecture of Gazi University, 25(4), 905-913.
7. Alguliyev, R. M., Aliguliyev, R. M., & Mahmudova, R. S. (2015). Multicriteria personnel selection by the modified fuzzy VIKOR method. The Scientific World Journal, 2015. doi:10.1155/2015/612767
8. Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Systems with applications, 39(9), 7961-7967.
doi: 10.1016/j.eswa.2012.01.100
9. Bali, Ö., Gümüş, S., & Dağdeviren, M. (2013). A group MADM method for personnel selection problem using Delphi technique based on intuitionistic fuzzy sets. Journal of Military and Information Science, 1(1), 1-13.
10. Baumann, M. R., Gohm, C. L., & Bonner, B. L. (2011). Phased training for high-reliability occupations: Live-fire exercises for civilian firefighters. Human factors, 53(5), 548-557. doi:10.1177/0018720811418224
11. Buchanan, B. G., Barstow, D., Bechtal, R., Bennett, J., Clancey, W., Kulikowski, C., ... & Waterman, D. A. (1983). Constructing an expert system. Building expert systems, 50, 127-167.
12. Butkiewicz, B. S. (2002, October). Selection of staff for enterprise using fuzzy logic. In Systems, Man and Cybernetics, 2002 IEEE International Conference on (Vol. 4, pp. 3-pp). IEEE. doi: 10.1109/icsmc.2002.1173304
13. Canós, L., & Liern, V. (2008). Soft computing-based aggregation methods for human resource management. European Journal of Operational Research, 189(3), 669-681. doi:10.1016/j.ejor.2006.01.054
14. Chien, C. F., & Chen, L. F. (2008). Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry. Expert Systems with applications, 34(1), 280-290.
doi:10.1016/j.eswa.2006.09.003
15. Dursun, M., & Karsak, E. E. (2010). A fuzzy MCDM approach for personnel selection. Expert Systems with applications, 37(6), 4324-4330.
doi:10.1016/j.eswa.2009.11.067
16. Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646. doi:10.1016/j.asoc.2008.09.003
17. Karsak, E. E. (2000). A fuzzy multiple objective programming approach for personnel selection. In Systems, Man, and Cybernetics, 2000 IEEE International Conference on (Vol. 3, pp. 2007-2012). IEEE. doi:10.1109/ICSMC.2000.886409
18. Kazan, H., Özçelik, S., & Hobikoğlu, E. H. (2015). Election of Deputy Candidates for Nomination with AHP-Promethee Methods. Procedia-Social and Behavioral Sciences, 195, 603-613.
doi:10.1016/j.sbspro.2015.06.141
19. Kusumawardani, R. P., & Agintiara, M. (2015). Application of fuzzy AHP-TOPSIS method for decision making in human resource manager selection process. Procedia Computer Science, 72, 638-646.
doi:10.1016/j.procs.2015.12.173
20. Lee, E. S., & Li, R. J. (1993). Fuzzy multiple objective programming and compromise programming with Pareto optimum. Fuzzy sets and systems, 53(3), 275-288.
doi:10.1016/0165-0114(93)90399-3
21. Mammadova, M., & Jabrayilova, Z. (2014). Application of Fuzzy Optimization Method in Decision-Making for Personnel Selection. Intelligent Control and Automation, 5(04), 190. doi:10.4236/ica.2014.54021
22. Matthews, G. (2016). Multidimensional profiling of task stress states for human factors: A brief review. Human factors, 58(6), 801-813. doi:10.1177/0018720816653688
23. Özdemir, A. (2013). A two-phase multi criteria dynamic programing approach for personnel selection process. Problems and Perspectives in Management, 11(2), 98-108.
24. Robertson, I. T., & Smith, M. (2001). Personnel selection. Journal of occupational and Organizational psychology, 74(4), 441-472. doi:10.1348/096317901167479
25. Sang, X., Liu, X., & Qin, J. (2015). An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise. Applied Soft Computing, 30, 190-204.
doi:10.1016/j.asoc.2015.01.002
26. Tabares-Ospina, H. A., Monsalve-Llano, D. A., & Diez-Gomez, D. (2013). Modelo de Sistema Experto para la Selección de Personal Docente Universitario. Tecno Lógicas, (30).
27. Vatansever, K., & Oncel, M. (2014). Implementation of integrated multi-criteria decision making techniques for academic staff recruitment. Journal of Management Marketing and Logistics, 1(2), 111-126.
28. Yu, D., Zhang, W., & Xu, Y. (2013). Group decision making under hesitant fuzzy environment with application to personnel evaluation. Knowledge-Based Systems, 52, 1-10. doi:10.1016/j.knosys.2013.04.010
29. Zhang, S. F., & Liu, S. Y. (2011). A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Systems with Applications, 38(9), 11401-11405.
doi:10.1016/j.eswa.2011.03.012
2. Afshari, R. A., Nikolić, M., & Ćoćkalo, D. (2014). Applications of fuzzy decision making for personnel selection problem: A review. Journal of Engineering Management and Competitiveness (JEMC), 4(2), 68-77.
3. Aggarwal, R. (2014). Identifying and Prioritizing Human Capital Measurement Indicators for Personnel Selection Using Fuzzy MADM. In Proceedings of the Third International Conference on Soft Computing for Problem Solving (pp. 427-439). Springer, New Delhi. doi:10.1007/978-81-322-1771-8_37
4. Aguilar Lasserre, A. A., Lafarja Solabac, M. V., Hernandez-Torres, R., Posada-Gomez, R., Juárez-Martínez, U., & Fernández Lambert, G. (2014). Expert system for competences evaluation 360 feedback using fuzzy logic. Mathematical Problems in Engineering, 2014. doi:10.1155/2014/789234
5. Akhlagh, E. (2011). A rough-set based approach to design an expert system for personnel selection. World Academy of Science, Engineering and Technology, 54, 202 205.
6. Aksakal, E., & Dagdeviren, M. (2010). An Integrated Approach for Personel Selection with DEMATEL and ANP Methods. Journal of The Faculty of Engineering and Architecture of Gazi University, 25(4), 905-913.
7. Alguliyev, R. M., Aliguliyev, R. M., & Mahmudova, R. S. (2015). Multicriteria personnel selection by the modified fuzzy VIKOR method. The Scientific World Journal, 2015. doi:10.1155/2015/612767
8. Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Systems with applications, 39(9), 7961-7967.
doi: 10.1016/j.eswa.2012.01.100
9. Bali, Ö., Gümüş, S., & Dağdeviren, M. (2013). A group MADM method for personnel selection problem using Delphi technique based on intuitionistic fuzzy sets. Journal of Military and Information Science, 1(1), 1-13.
10. Baumann, M. R., Gohm, C. L., & Bonner, B. L. (2011). Phased training for high-reliability occupations: Live-fire exercises for civilian firefighters. Human factors, 53(5), 548-557. doi:10.1177/0018720811418224
11. Buchanan, B. G., Barstow, D., Bechtal, R., Bennett, J., Clancey, W., Kulikowski, C., ... & Waterman, D. A. (1983). Constructing an expert system. Building expert systems, 50, 127-167.
12. Butkiewicz, B. S. (2002, October). Selection of staff for enterprise using fuzzy logic. In Systems, Man and Cybernetics, 2002 IEEE International Conference on (Vol. 4, pp. 3-pp). IEEE. doi: 10.1109/icsmc.2002.1173304
13. Canós, L., & Liern, V. (2008). Soft computing-based aggregation methods for human resource management. European Journal of Operational Research, 189(3), 669-681. doi:10.1016/j.ejor.2006.01.054
14. Chien, C. F., & Chen, L. F. (2008). Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry. Expert Systems with applications, 34(1), 280-290.
doi:10.1016/j.eswa.2006.09.003
15. Dursun, M., & Karsak, E. E. (2010). A fuzzy MCDM approach for personnel selection. Expert Systems with applications, 37(6), 4324-4330.
doi:10.1016/j.eswa.2009.11.067
16. Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646. doi:10.1016/j.asoc.2008.09.003
17. Karsak, E. E. (2000). A fuzzy multiple objective programming approach for personnel selection. In Systems, Man, and Cybernetics, 2000 IEEE International Conference on (Vol. 3, pp. 2007-2012). IEEE. doi:10.1109/ICSMC.2000.886409
18. Kazan, H., Özçelik, S., & Hobikoğlu, E. H. (2015). Election of Deputy Candidates for Nomination with AHP-Promethee Methods. Procedia-Social and Behavioral Sciences, 195, 603-613.
doi:10.1016/j.sbspro.2015.06.141
19. Kusumawardani, R. P., & Agintiara, M. (2015). Application of fuzzy AHP-TOPSIS method for decision making in human resource manager selection process. Procedia Computer Science, 72, 638-646.
doi:10.1016/j.procs.2015.12.173
20. Lee, E. S., & Li, R. J. (1993). Fuzzy multiple objective programming and compromise programming with Pareto optimum. Fuzzy sets and systems, 53(3), 275-288.
doi:10.1016/0165-0114(93)90399-3
21. Mammadova, M., & Jabrayilova, Z. (2014). Application of Fuzzy Optimization Method in Decision-Making for Personnel Selection. Intelligent Control and Automation, 5(04), 190. doi:10.4236/ica.2014.54021
22. Matthews, G. (2016). Multidimensional profiling of task stress states for human factors: A brief review. Human factors, 58(6), 801-813. doi:10.1177/0018720816653688
23. Özdemir, A. (2013). A two-phase multi criteria dynamic programing approach for personnel selection process. Problems and Perspectives in Management, 11(2), 98-108.
24. Robertson, I. T., & Smith, M. (2001). Personnel selection. Journal of occupational and Organizational psychology, 74(4), 441-472. doi:10.1348/096317901167479
25. Sang, X., Liu, X., & Qin, J. (2015). An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise. Applied Soft Computing, 30, 190-204.
doi:10.1016/j.asoc.2015.01.002
26. Tabares-Ospina, H. A., Monsalve-Llano, D. A., & Diez-Gomez, D. (2013). Modelo de Sistema Experto para la Selección de Personal Docente Universitario. Tecno Lógicas, (30).
27. Vatansever, K., & Oncel, M. (2014). Implementation of integrated multi-criteria decision making techniques for academic staff recruitment. Journal of Management Marketing and Logistics, 1(2), 111-126.
28. Yu, D., Zhang, W., & Xu, Y. (2013). Group decision making under hesitant fuzzy environment with application to personnel evaluation. Knowledge-Based Systems, 52, 1-10. doi:10.1016/j.knosys.2013.04.010
29. Zhang, S. F., & Liu, S. Y. (2011). A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Systems with Applications, 38(9), 11401-11405.
doi:10.1016/j.eswa.2011.03.012
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