Intuitionistic Fuzzy Number Based Group Decision Making Approach For Personnel Selection

Yıl 2018, Cilt: 23 Sayı: 3, 11 - 26, 31.12.2018

Burak Efe , Ömer Faruk Efe

https://doi.org/10.17482/uumfd.338406

Öz

The most appropriate personnel
selection is a very important issue for an organization’s success due to the
increasing competition in global market. Traditionally, Saaty’s consistency
method is used to check the consistency of the experts’ judgments in personnel
selection problem and the inconsistency judgments can be sent to return to the
experts for reevaluation, which is time consuming and sometimes undesired by
experts, or can be extracted from decision making process. A perfect
multiplicative consistent intuitionistic preference relation (IPR) will be
repaired the inconsistent IPRs of the experts into a consistent one
automatically. There is no paper about personnel selection using integrated
intuitionistic fuzzy analytic hierarchy process method (IFAHP)-IFVIKOR
(intuitionistic fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje)
approach under group decision making with perfect multiplicative consistent IPR.
This paper presents an integrated multi-criteria decision making method for
personnel selection with perfect multiplicative consistent IPR under
intuitionistic fuzzy environment. Priority value of criteria has been defined
by utilizing IFAHP method and the most appropriate personnel among candidates
has been found by utilizing intuitionistic fuzzy VIKOR. The application of
personnel selection is conducted to illustrate the effectiveness of the
proposed method in a logistic firm. The personel selection is realized
according to a questionnaire responded by three experts in human resources management area. Five criteria for
personel selection are defined through literature review and the judgments of
expert team. K1 (self-confidence) is defined as the most important criteria for
personnel selection of the specified logistic firm by using IFAHP. Alt₃
is defined as the most suitable personnel for the specified logistic firm by
using IFVIKOR.

Anahtar Kelimeler

Personnel selection, intuitionistic preference relation, fuzzy multi-criteria group decision making, intuitionistic fuzzy set

PERSONEL SEÇİMİ İÇİN SEZGİSEL BULANIK SAYI TEMELLİ GRUP KARAR VERME YAKLAŞIMI

Öz

Küresel pazarda artan rekabetten dolayı en
uygun personel seçimi bir organizasyonun başarısında çok önemli bir konudur.
Saaty’nin tutarlılık metodu uzman görüşlerinin tutarlılığını kontrol etmek için
kullanılır. Tutarsız görüşler yeniden değerlendirme için uzmanlara geri
gönderilir. Bu çalışmada mükemmel çarpımsal tutarlı sezgisel tercih ilişkisi,
tutarsız uzman görüşlerini otomatik olarak tutarlı hale getirmek için
kullanılır. Sezgisel bulanık analitik hiyerarşi prosesi (SBAHP) ve SBVIKOR
(sezgisel bulanık VlseKriterijumska Optimizacija I
Kompromisno Resenje) yaklaşımı personel seçimi probleminde daha
önce kullanılmamıştır. Bu makale sezgisel bulanık ortamda mükemmel çarpımsal
tutarlı sezgisel tercih ilişkili personel seçimi için bütünleşik çok kriterli
karar verme yaklaşımını sunmaktadır. Kriterlerin öncelik dereceleri SBAHP
metodu kullanılarak belirlenmiş ve adaylar arasından en uygun personel SBVIKOR
metodu kullanılarak belirlenmiştir. Personel seçimi uygulaması bir lojistik
firmasında önerilen metodun etkinliğini göstermek için gerçekleştirilmiştir.
İnsan kaynakları alanında uzman üç kişi tarafından bir anket yardımıyla
personel seçimi yapılmıştır. Personel seçimi için uzman görüşleri ve
literatürden yararlanılarak beş kriter belirlenmiştir. SBAHP yaklaşımı
sonucunda K1 (kendine güven) kriteri lojistik firması için personel seçiminde
en önemli kriter olarak belirlenmiştir. SBVIKOR yaklaşımı sonucunda lojistik
firması için en uygun adayın alternatif 3 olduğu belirlenmiştir.

Anahtar Kelimeler

Personel seçimi, sezgisel tercih ilişkisi, bulanık çok kriterli grup karar verme, sezgisel bulanık küme

Kaynakça

• Aarushi, Malik, S.K. (2016). Generalized MCDM-based decision support system for personnel prioritization, Advances in Intelligent Systems and Computing, 408, 155-168. doi: 10.1007/978-981-10-0129-1_17
• Abdullah, L., Najib, L. (2016). Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: Choosing energy technology in Malaysia, International Journal of Sustainable Energy, 35(4), 360-377. doi: 10.1080/14786451.2014.907292
• Atanassov, K.T. (1986). Intuitionistic fuzzy sets, Fuzzy Sets Syst. 20,87–96. doi: 10.1016/S0165-0114(86)80034-3
• Awasthi, A., Govindan, K., & Gold, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106-117. doi: 10.1016/j.ijpe.2017.10.013
• Ayağ, Z. (2010). A combined fuzzy AHP-simulation approach to CAD software selection, International Journal of General Systems, 39(7), 731-756. doi: 10.1080/03081079.2010.495190
• Aydın, S., Kahraman, C. (2014). Vehicle selection for public transportation using an integrated multi criteria decision making approach: A case of Ankara, Journal of Intelligent and Fuzzy Systems, 26(5), 2467-2481. doi: 10.3233/IFS-130917
• 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. doi: 10.1016/j.eswa.2012.01.100
• Cevik Onar, S., Oztaysi, B., Kahraman, C. (2014). Strategic Decision Selection Using Hesitant fuzzy TOPSIS and Interval Type-2 Fuzzy AHP: A case study, International Journal of Computational Intelligence Systems, 7 (5), pp. 1002-1021. doi: 10.1080/18756891.2014.964011
• Cevikcan, E., Cebi, S., Kaya, I. (2009). Fuzzy VIKOR and fuzzy axiomatic design versus to fuzzy TOPSIS: An application of candidate assessment, Journal of Multiple-Valued Logic and Soft Computing, 15(2-3), 181-208. doi: 10.1155/2012/490647
• Chatterjee, K., Kar, M. B., Kar, S. (2013). Strategic Decisions Using Intuitionistic Fuzzy Vikor Method for Information System (IS) Outsourcing, 2013 International Symposium on Computational and Business Intelligence, 123-126. doi: 10.1109/ISCBI.2013.33
• Devi, K. (2011). Extension of VIKOR method in intuitionistic fuzzy environment for robot selection, Expert Systems with Applications, 38(11), 14163-14168. doi: 10.1016/j.eswa.2011.04.227
• 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
• Efe, B., Kurt, M., Efe, Ö. F. (2017). An integrated intuitionistic fuzzy set and mathematical programming approach for an occupational health and safety policy. Gazi University Journal of Science, 30(2), 73-95. doi: 30799/333114
• Gibney, R., Shang, J. (2007). Decision making in academia: A case of the dean selection process, Mathematica and Computer Modelling, 46(7-8), 1030–1040. doi: 10.1016/j.mcm.2007.03.024
• Hernandez, E.A., Uddameri, V. (2010). Selecting agricultural best management practices for water conservation and quality improvements using Atanassov’s intuitionistic fuzzy sets, Water Resour. Manage. 24, 4589–4612. doi: 10.1007/s11269-010-9681-1
• Ji, P., Zhang, H.-Y., Wang, J.-Q. (2018). A projection-based TODIM method under multi-valued neutrosophic environments and its application in personnel selection, Neural Computing and Applications, 29(1), 221-234. doi: 10.1007/s00521-016-2436
• Karabasevic, D., Zavadskas, E.K., Turskis, Z., Stanujkic, D. (2016). The Framework for the Selection of Personnel Based on the SWARA and ARAS Methods Under Uncertainties, Informatica (Netherlands), 27(1), 49-65. doi: 10.15388/Informatica.2016.76
• 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. doi: 10.1016/j.apm.2013.01.026
• Liu, H.C., Qin, J.T., Mao, L.X., Zhang, Z.Y. (2015). Personnel Selection Using Interval 2-Tuple Linguistic VIKOR Method, Human Factors and Ergonomics in Manufacturing & Service Industries, 25(3), 370-384. doi: 10.1002/hfm.20553
• Liu, H.C., You, J.X., You, X.Y., Shan, M.M. (2015). A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method, Applied Soft Computing Journal, 28, 579-588. doi: 10.1016/j.asoc.2014.11.036
• Lin, H.T. (2010). Personnel selection using analytic network process and fuzzy data envelopment analysis approaches, Comput. Ind. Eng. 59(4) 937–944. doi: 10.1016/j.cie.2010.09.004
• Opricovic, S. (1998). Multi-criteria optimization of civil engineering systems. Belgrade: Faculty of Civil Engineering. doi: 1600129
• Opricovic, S., Tzeng, G. (2007). Extended VIKOR method in comparison with outranking methods, European Journal of Operational Research, 178(2) 514-529. doi: 10.1016/j.ejor.2006.01.020
• 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. doi: 10.1016/S0377-2217(03)00020-1
• Parameshwaran, R., Praveen, K.S., Saravanakumar, K. (2015). An integrated fuzzy MCDM based approach for robot selection considering objective and subjective criteria, Applied Soft Computing Journal, 26, 31-41. doi: 10.1016/j.asoc.2014.09.025
• Prasad, K. D., Prasad, M. V., Rao, S. B., Patro, C. S. (2016). Supplier Selection through AHP-VIKOR Integrated Methodology. SSRG International Journal of Industrial Engineering, 3(5), 1-6. doi: 10.14445/23499362/IJIE-V3I5P101
• Qin, J., Liu, X., Pedrycz, W. (2016). Frank aggregation operators and their application to hesitant fuzzy multiple attribute decision making, Applied Soft Computing Journal, 41, 428-452. doi: 10.1016/j.asoc.2015.12.030
• Saaty, T.L. (1980). The analytic hierarchy process. New York: McGraw-Hill. doi: 0377-2217/90/$03.50
• Salehi, K. (2015). A hybrid fuzzy MCDM approach for project selection problem, Decision Science Letters, 4(1), 109-116. doi: 10.5267/j.dsl.2014.8.003
• Sambasivan, M., Fei, N.Y. (2008). Evaluation of Critical Success Factors of Implementation of ISO 14001 Using Analytic Hierarchy Process (AHP): A Case Study From Malaysi. Journal of Cleaner Production, 16, 1424- 1433. doi: 10.1016/j.jclepro.2007.08.003
• 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
• Wu, Y., Geng, S. (2014). Evaluation of coal supplier based on intuitionistic fuzzy set and VIKOR method, Journal of Information and Computational Science, 11(11), 3753-3763. doi: 10.12733/jics20104136
• Xu, Z. S., Intuitionistic fuzzy aggregation operators, IEEE Transaction of Fuzzy Systems, 15(6) (2007) 1179–1187. doi: 10.1109/TFUZZ.2006.890678
• Xu, Z., Liao, H. (2014). Intuitionistic fuzzy analytic hierarchy process, IEEE Transactions on Fuzzy Systems, 22(4) 749-761. doi: 10.1109/TFUZZ.2013.2272585
• Xu, Z.S., Multi-person multi-attribute decision making models under intuitionistic fuzzy environment, Fuzzy Optim. Decis. Making 6 (2007) 221–236. doi: 10.1007/s10700-007-9009-7
• You, X.Y., You, J.X., Liu, H.C., Zhen, L. (2015). Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information, Expert Systems with Applications, 42(4), 1906-1916. doi: 10.1016/j.eswa.2014.10.004
• 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
• Yu, X., Zhang, H., Bouras, A., Ouzrout, Y., Sekhari, A. (2018). Multi-Criteria Decision Making for PLM Maturity Analysis based on an Integrated Fuzzy AHP and VIKOR Methodology. Journal of Advanced Manufacturing Systems, 17(02), 155-179. doi: 10.1142/S0219686718500105
• 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