MULTIMOORA-FG: A multi-objective decision making method for linguistic reasoning with an application to personnel selection

Informatica (Netherlands)

Volumn 23, Issue 2, 2012, Pages 173-190

  Baležentis, Alvydas ^a   Baležentis, Tomas ^b   Brauers, Willem K M ^c  

^a MYKOLAS ROMERIS UNIVERSITY   (Lithuania)

^b Lithuanian Institute of Agrarian Economics   (Lithuania)

^c UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

employment decisions; fuzzy number; human resources management; linguistic reasoning; multi objective optimization; MULTIMOORA; MULTIMOORA FG; personnel management; personnel selection

Indexed keywords

FUZZY RULES; FUZZY SETS; LINGUISTICS; MULTIOBJECTIVE OPTIMIZATION; PERSONNEL; PERSONNEL SELECTION;

FUZZY NUMBERS; HUMAN RESOURCES MANAGEMENT; LINGUISTIC REASONINGS; MULTIMOORA; MULTIMOORA-FG; PERSONNEL MANAGEMENT;

DECISION MAKING;

EID: 84863657236     PISSN: 08684952     EISSN: None     Source Type: Journal    
DOI: 10.15388/informatica.2012.355     Document Type: Article

References (62)

1. Ahituv, N., Spector, Y. (1990). Evaluating Information under two Criteria: Expected Payoff and Risk. Working paper No. 70/90. I. I. B. R., Tel Aviv University, Israel, 5.
2. Belton, V., Stewart, T. J. (2002). Multiple criteria decision analysis: an integrated approach. Boston, Kluwer Academic.
3. Brauers, W. K. (2004). Optimization Methods for a Stakeholder Society, a Revolution in Economic Thinking by Multi-Objective Optimization. Boston, Kluwer Academic.
4. Brauers, W. K. (2007). What is meant by normalization in decision making? International Journal of Management and Decision Making, 8(5/6), 445-460.
5. Brauers, W. K. M., Ginevicius, R. (2009). Robustness in regional development studies: The case of Lithuania. Journal of Business Economics and Management, 10(2), 121-140.
6. Brauers, W. K. M., Ginevicius, R. (2010). The economy of the Belgian regions tested with MULTIMOORA. Journal of Business Economics and Management, 11(2), 173-209.
7. Brauers, W. K. M., Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 445-469. (Pubitemid 44926388)
8. Brauers, W. K., Zavadskas, E. K. (2009). Robustness of the multi-objective MOORA method with a test for the facilities sector. Technological and Economic Development of Economy, 15(2), 352-375.
9. Brauers, W. K. M., Zavadskas, E. K. (2010a). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24.
10. Brauers, W. K. M., Zavadskas, E. K. (2010b). Robustness in the MULTIMOORA model: the example of Tanzania. Transformations in Business & Economics, 9(3), 67-83.
11. Brauers, W. K. M., Zavadskas, E. K. (2011a). MULTIMOORA optimization used to decide on a bank loan to buy property. Technological and Economic Development of Economy, 17(1), 174-188.
12. Brauers, W. K. M., Zavadskas, E. K. (2011b). From a centrally planned economy to multiobjective optimization in an enlarged project management: the case of China. Economic Computation and Economic Cybernetics Studies and Research, (1), 167-188.
13. Brauers, W. K. M., Ginevicius, R., Zavadskas E. K., Antucheviciene J. (2007). The European Union in a transition economy. Transformation in Business & Economics, 6(2), 21-37.
14. Brauers, W. K. M., Zavadskas, E. K., Turskis, Z., Vilutiene, T. (2008a). Multi-objective contractor's ranking by applying the MOORA method. Journal of Business Economics and Management, 9(4), 245-255.
15. Brauers, W. K. M., Zavadskas, E. K., Peldschus, F., Turskis, Z. (2008b). Multi-objective decision-making for road design. Transport, 23(3), 183-193.
16. Brauers, W. K. M., Baležentis, A., Baležentis, T. (2011). MULTIMOORA for the EU Member States updated with fuzzy number theory. Technological and Economic Development of Economy, 17(2), 259-290.
17. Chakraborty, S. (2011). Applications of the MOORA method for decision making in manufacturing environment. The International Journal of Advanced Manufacturing Technology, 54, 1155-1166.
18. Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114, 1-9.
19. Chen, S. J., Chen, S. M. (2003). A new method for handling multicriteria fuzzy decision-making problems using FN-IOWA operators. Cybernetics and Systems: An International Journal, 34, 109-137.
20. Chou, S. Y., Chang, Y. H., Shen, C. Y. (2008). A fuzzy simple additive weighting system under group decisionmaking for facility location selection with objective/subjective attributes. European Journal of Operational Research, 189, 132-145.
21. Dursun, M., Karsak, E. (2010). A fuzzy MCDM approach for personnel selection. Expert Systems with Applications, 37, 4324-4330.
22. Kahraman, C. (2008). Multi-criteria decision making methods and fuzzy sets. In: Kahraman, C. (Ed.) Fuzzy Multi-Criteria Decision Making. Springer, Berlin.
23. Kahraman, C., Kaya, ?I. (2010). Investment analyses using fuzzy probability concept. Technological and Economic Development of Economy, 16(1), 43-57.
24. Kaya, T., Kahraman, C. (2011). A fuzzy approach to e-banking website quality assessment based on an integrated AHP-ELECTRE method. Technological and Economic Development of Economy, 17(2), 313-334.
25. Kalibatas, D., Turskis, Z. (2008). Multicriteria evaluation of inner climate by using MOORA method. Information Technology and Control, 37(1), 79-83.
26. Kelemenis, A., Askounis, D. (2010). A new TOPSIS-based multi-criteria approach to personnel selection. Expert Systems with Applications, 37, 4999-5008.
27. Kelemenis, A., Ergazakis, K., Askounis, D. (2011). Support managers' selection using an extension of fuzzy TOPSIS. Expert Systems with Applications, 38, 2774-2782.
28. Keufmann, A., Gupta, M. M. (1991). Introduction to Fuzzy Arithmetic: Theory and Application. Van Nostrand-Reinhold, New York.
29. Kracka, M., Brauers, W. K. M., Zavadskas, E. K. (2010). Ranking heating losses in a building by applying the MULTIMOORA. Inžinerin?e ekonomika-Engineering Economics, 21(4), 352-359.
30. Liang, G. S. 1999. Fuzzy MCDM based on ideal and anti-ideal concepts. European Journal of Operational Research, 112, 682-691.
31. Liang, G. S., Ding, J. F. (2003). Fuzzy MCDM based on the concept of α-cut. Journal of Multi-Criteria Decision Analysis, 12(6), 299-310.
32. Liu, P. (2009). A novel method for hybrid multiple attribute decision making. Knowledge-Based Systems, 22(5), 388-391. doi:10. 1016/j. knosys. 2009. 02. 001
33. Liu, W., Liu, P. (2010). Hybrid multiple attribute decision making method based on relative approach degree of grey relation projection. African Journal of Business Management, 4(17), 3716-3724.
34. Loken, E. (2007). Use of multicriteria decision analysis methods for energy planning problems. Renewable and Sustainable Energy Reviews, 11, 1584-1595. (Pubitemid 46349808)
35. MacCrimmon, K. R. (1968). Decision Making Among Multiple Attribute Alternatives: A Survey and Consolidated Approach. RAND Memorandum, RM-4823-ARPA. The RAND Corporation, Santa Monica.
36. Merigo, J. M., Casanovas, M. (2011). Induced and uncertain heavy OWA operators. Computers & Industrial Engineering, 60, 106-116.
37. Merigo, J. M., Gil-Laufente, A. (2009). The induced generalized OWA operator. Information Sciences, 179, 729-741.
38. Merigo, J. M., Gil-Laufente, A. M. (2011). OWA operators in human resource management. Economic Computation and Economic Cybernetics Studies and Research, 45(2), 153-168.
39. Merigo, J. M., Wei, G. W. (2011) Probabilistic aggregation operators and their application in uncertain multiperson decision-making. Technological and Economic Development of Economy, 17(2), 335-351.
40. Miller, G. A. (1965). The magical number seven plus or minus two: some limits on our capacity for processing information, Psychological Review, 63, 81-97.
41. Peldschus, F. (2009). The analysis of the quality of the results obtained with the methods of multi-criteria decisions. Technological and Economic Development of Economy, 15(4), 580-592.
42. Peldschus, F., Zavadskas, E. K. (2005). Fuzzy matrix games multi-criteria model for decision-making in engineering. Informatica, 16(1), 107-120. (Pubitemid 40900339)
43. Roy, B. (1996). Multicriteria Methodology for Decision Aiding. Kluwer Academic Dordrecht.
44. Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods: a Comparative Study. Kluwer Academic Dordrecht.
45. Torlak, G., Sevkli, M., Sanal, M., Zaim, S. (2011). Analyzing business competition by using fuzzy TOPSIS method: an example of Turkish domestic airline industry. Expert Systems with Applications, 38(4), 3396-9406. doi:10. 1016/j. eswa. 2010. 08. 125
46. Wang, Y. M., Parkan, C. (2007). A preemptive goal programming method for aggregating OWA operator weights in group decision making. Information Sciences, 177, 1867-1877. (Pubitemid 46176946)
47. Wierzbicki, A. P. (1982). A mathematical basis for satisficing decision making, Mathematical Modelling, 3(5), 391-405. (Pubitemid 13196014)
48. Xu, Z. S., Da, Q. L. (2003). An overview of operators for aggregating information. International Journal of Intelligent Systems, 18, 953-969.
49. Yager, R. R. (1988). On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man and Cybernetics, 18, 183-190.
50. Yao, J. S., Wu, K. (2000). Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets and Systems, 116, 275-288.
51. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(1), 338-353.
52. Zadeh, L. A. (1975a). The concept of a linguistic variable and its application to approximate reasoning-I. Information Sciences, 8(3), 199-249.
53. Zadeh, L. A. (1975b). The concept of a linguistic variable and its application to approximate reasoning-II. Information Sciences, 8(4), 301-357.
54. Zadeh, L. A. (1975c). The concept of a linguistic variable and its application to approximate reasoning-III. Information Sciences, 9(1), 43-80.
55. Zavadskas, E. K., Antucheviciene, J. (2006). Development of an indicator model and ranking of sustainable revitalization alternatives of derelict property: a Lithuanian case study. Sustainable Development, 14(5), 287-299. (Pubitemid 44970816)
56. Zavadskas, E. K., Antucheviciene, J. (2007). Multiple criteria evaluation of rural building's regeneration alternatives. Building and Environment, 42(1), 436-451. (Pubitemid 44426583)
57. Zavadskas, E. K., Turskis, Z. (2011). Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2), 397-427.
58. Zavadskas, E. K., Turskis, Z., Tamošaitiene, J., Marina, V. (2008). Multicriteria selection of project managers by applying grey criteria. Technological and Economic Development of Economy, 14(4), 462-477.
59. Zavadskas, E. K., Turskis, Z., Ustinovichius, L., Shevchenko, G. (2010). Attributes weights determining peculiarities in multiple attribute decision making methods. Inzinerine Ekonomika-Engineering Economics, 21(1), 32-43.
60. Zhang, X., Liu, P. (2010). Method for aggregating triangular fuzzy intuitionistic fuzzy information and its application to decision making. Technological and Economic Development of Economy, 16(2), 280-290.
61. 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. doi, 10. 1016/j. eswa. 2011. 03. 012
62. Zhao, R., Govind, R. (1991). Algebraic characteristics of extended fuzzy numbers, Information Science, 54(1), 103-130.