Personnel selection using interval 2-tuple linguistic VIKOR method

Human Factors and Ergonomics In Manufacturing

Volumn 25, Issue 3, 2015, Pages 370-381

  Liu, Hu Chen ^a,b   Qin, Jiang Tao ^c   Mao, Ling Xiang ^d   Zhang, Zhi Ying ^e  

^a HEFEI UNIVERSITY OF TECHNOLOGY   (China)

^b TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

^c School of Mining and Environment Chongqing Vocational Institute of Engineering   (China)

^d NANJING UNIVERSITY   (China)

^e TONGJI UNIVERSITY   (China)

Author keywords

Interval 2 tuple; Multicriteria group decision making; Personnel selection; VIKOR method

Indexed keywords

COMPUTATIONAL LINGUISTICS; DECISION MAKING; HUMAN RESOURCE MANAGEMENT; LINGUISTICS; NUMERICAL METHODS;

2-TUPLE; 2-TUPLE LINGUISTIC; GROUP DECISION MAKING; LINGUISTIC ASSESSMENT; LINGUISTIC INFORMATION; LINGUISTIC TERMS; MULTI CRITERIA GROUP DECISION MAKING; VIKOR METHOD;

PERSONNEL SELECTION;

EID: 84926361706     PISSN: 10908471     EISSN: 15206564     Source Type: Journal    
DOI: 10.1002/hfm.20553     Document Type: Article

References (42)

1. Baležentis, A., Baležentis, T., &, Brauers, W. K. M., (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Systems with Applications, 39 (9), 7961-7967.
2. Boran, F. E., Genc, S., &, Akay, D., (2011). Personnel selection based on intuitionistic fuzzy sets. Human Factors and Ergonomics in Manufacturing & Service Industries, 21 (5), 493-503.
3. Canõs, L., &, Liern, V., (2008). Soft computing-based aggregation methods for human resource management. European Journal of Operational Research, 189 (3), 669-681.
4. Chen, C. T., &, Tai, W. S., (2005). Measuring the intellectual capital performance based on 2-tuple fuzzy linguistic information. Proceedings of the 10th Annual Meeting of Asia Pacific Region of Decision Sciences Institute (Vol. 20), Taiwan. June 28-July 2.
5. Dursun, M., &, Karsak, E. E., (2010). A fuzzy MCDM approach for personnel selection. Expert Systems with Applications, 37 (6), 4324-4330.
6. Ebrahimnejad, S., Mousavi, S. M., Tavakkoli-Moghaddam, R., Hashemi, H., &, Vahdani, B., (2012). A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling, 36 (9), 4197-4217.
7. Güngör, Z., Serhadlioʇlu, G., &, Kesen, S. E., (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9 (2), 641-646.
8. Herrera, F., &, Martínez, L., (2000a). A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems, 8 (6), 746-752.
9. Herrera, F., &, Martínez, L., (2000b). An approach for combining linguistic and numerical information based on the 2-tuple fuzzy linguistic representation model in decision-making. International Journal of Uncertainty, Fuzziness and Knowledge Based Systems, 8 (5), 539-562.
10. Herrera, F., &, Martínez, L., (2001a). The 2-tuple linguistic computational model: Advantages of its linguistic description, accuracy and consistency. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9 (Suppl. 1), 33-48.
11. Herrera, F., &, Martínez, L., (2001b). A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics, 31 (2), 227-234.
12. Herrera-Viedma, E., Herrera, F., Martinez, L., Herrera, J. C., &, Lõpez, A. G., (2004). Incorporating filtering techniques in a fuzzy linguistic multi-agent model for information gathering on the web. Fuzzy Sets and Systems, 148 (1), 61-83.
13. Jeya Girubha, R., &, Vinodh, S., (2012). Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Materials & Design, 37, 478-486.
14. Ju, Y., &, Wang, A., (2013). Extension of VIKOR method for multi-criteria group decision making problem with linguistic information. Applied Mathematical Modelling, 37 (5), 3112-3125.
15. Kabak, M., Burmaoʇlu, S., &, Kazançoʇlu, Y., (2012). A fuzzy hybrid MCDM approach for professional selection. Expert Systems with Applications, 39 (3), 3516-3525.
16. Karwowski, W., &, Evans, R. W., (1986). Fuzzy concepts in production management research: a review. International Journal of Production Research, 24 (1), 129-147.
17. Karwowski, W., Kosiba, E., Benabdallah, S., &, Salvendy, G., (1990). A framework for development of fuzzy GOMS model for human-computer interaction. International Journal of Human-Computer Interaction, 2 (4), 287-305.
18. Kelemenis, A., &, Askounis, D., (2010). A new TOPSIS-based multi-criteria approach to personnel selection. Expert Systems with Applications, 37 (7), 4999-5008.
19. Kelemenis, A., Ergazakis, K., &, Askounis, D., (2011). Support managers' selection using an extension of fuzzy TOPSIS. Expert Systems with Applications, 38 (3), 2774-2782.
20. Kuo, M. S., &, Liang, G. S., (2011). Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Systems with Applications, 38 (3), 1304-1312.
21. Kuo, M. S., &, Liang, G. S., (2012). A soft computing method of performance evaluation with MCDM based on interval-valued fuzzy numbers. Applied Soft Computing, 12 (1), 476-485.
22. Lin, H. T., (2010). Personnel selection using analytic network process and fuzzy data envelopment analysis approaches. Computers & Industrial Engineering, 59 (4), 937-944.
23. Liu, H. C., Liu, L., &, Li, P., (2013). Failure mode and effects analysis using intuitionistic fuzzy hybrid weighted Euclidean distance operator. International Journal of Systems Science. doi: 10.1080/00207721.2012.760669
24. Liu, H. C., Liu, L., Liu, N., &, Mao, L. X., (2012). Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 39 (17), 12926-12934.
25. Liu, H. C., Mao, L. X., Zhang, Z. Y., &, Li, P., (2013). Induced aggregation operators in the VIKOR method and its application in material selection. Applied Mathematical Modelling, 37 (9), 6325-6338.
26. Opricovic, S., (1998). Multi-criteria optimization of civil engineering systems (Unpublished doctoral dissertation). Faculty of Civil Engineering, Belgrade.
27. Opricovic, S., (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38 (10), 12983-12990.
28. Opricovic, S., &, Tzeng, G. H., (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156 (2), 445-455.
29. Opricovic, S., &, Tzeng, G. H., (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178 (2), 514-529.
30. San Cristõbal, J. R., (2011). Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method. Renewable Energy, 36 (2), 498-502.
31. Sanayei, A., Farid Mousavi, S., &, Yazdankhah, A., (2010). Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Systems with Applications, 37 (1), 24-30.
32. Tai, W. S., &, Chen, C. T., (2009). A new evaluation model for intellectual capital based on computing with linguistic variable. Expert Systems with Applications, 36 (2, Pt. 2), 3483-3488.
33. Wang, W. P., (2009). Evaluating new product development performance by fuzzy linguistic computing. Expert Systems with Applications, 36 (6), 9759-9766.
34. Wang, Y. L., &, Tzeng, G. H., (2012). Brand marketing for creating brand value based on a MCDM model combining DEMATEL with ANP and VIKOR methods. Expert Systems with Applications, 39 (5), 5600-5615.
35. Wu, H. Y., Chen, J. K., Chen, I. S., &, Zhuo, H. H., (2012). Ranking universities based on performance evaluation by a hybrid MCDM model. Measurement, 45 (5), 856-880.
36. Yager, R. R., (1988). On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems, Man and Cybernetics, 18 (1), 183-190.
37. Yücenur, G. N., &, Demirel, N. Ç., (2012). Group decision making process for insurance company selection problem with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 39 (3), 3702-3707.
38. Zadeh, L. A., (1975). The concept of a linguistic variable and its application to approximate reasoning: I. Information Sciences, 8 (3), 199-249.
39. Zeleny, M., (1982). Multiple criteria decision making. New York: McGraw-Hill.
40. Zhang, H., (2012). The multiattribute group decision making method based on aggregation operators with interval-valued 2-tuple linguistic information. Mathematical and Computer Modelling, 56 (1-2), 27-35.
41. Zhang, H., (2013). Some interval-valued 2-tuple linguistic aggregation operators and application in multiattribute group decision making. Applied Mathematical Modelling, 37 (6), 4269-4282.
42. 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.