Personel Seçimi İçin Sezgisel Bulanık Sayı Temelli Grup Karar Verme Yaklaşımı

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 önerilenmetodun 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.

INTUITIONISTIC FUZZY NUMBER BASED GROUP DECISION MAKING APPROACH FOR PERSONNEL SELECTION

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

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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 multivalued 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