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Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması

Yıl 2017, Cilt: 12 Sayı: 48, 249 - 256, 31.10.2017

Öz

Makine seçimi konusu işletmelerde üretim
planlaması açısından oldukça önemli bir karar problemidir. Uygun makinenin
seçilmesi sürecinde üretim hızını, maliyetleri, kapasiteyi ve verimliliği etkileyen
birçok kriterin birlikte göz önünde bulundurulmasının gerekliliği nedeniyle,
makine seçimi problemi için etkin bir karar verme aracına ihtiyaç
duyulmaktadır. Birçok alanda uygulanabilirliği ile ön plana çıkan çok kriterli
karar verme (ÇKKV) teknikleri bu konuda etkili bir çözüm aracı olarak kullanılabilmektedir.
Bu çalışmanın temel amacı da, ÇKKV tekniklerinin kullanılması yoluyla doğal taş
sektöründe yer alan bir işletme için makine seçim problemine çözüm aramaktır.
Bu amaçla, karar alma sürecindeki belirsizleri de dikkate alabilen bulanık ÇKKV
yaklaşımı; bütünleşik Bulanık DEMATEL-Bulanık VIKOR yöntemi makine seçimi
problemine uygulanmıştır.  Literatüre ve
karar probleminin yapısına uygun olarak belirlenen kriterler öncelikle firma
bünyesindeki yönetici ve mühendislerden oluşan karar vericilerin görüşleri doğrultusunda
değerlendirilmiştir. Alınan bilgiler ışığında Bulanık DEMATEL yöntemi ile
kriterler arasındaki ilişkiler belirlenerek kriter ağırlıkları elde edilmiştir.
Daha sonra, ilgili işletme için Bulanık VIKOR yöntemi yardımıyla üç mermer
kesim makinesi alternatifi arasından en uygun olanın seçilmesi sağlanmıştır. 

Kaynakça

  • Agdaie, M.H., Zolfani, S.H. ve Zavadskas, E.K. 2013. Decision Making in Machine Tool Selection: An İntagrated Approach With SWARA and COPRAS-G Methods. Engineering Economics, 24(1): 5-17.
  • Arslan, M.Ç., Çatay, B. ve Budak, E. 2004. A Decision Support System For Machine Tool Selection. Journal of Manufacturing Technology Management. 15(1): 101-109.
  • Atmani, A. ve Lashkari, R. S. 1998. A model of Machine-tool Selection and Operation Allocation in FMS. International Journal of Production Research, 36(5): 1339-1349.
  • Ayağ, Z. 2007. A Hybrid Approach to Machine Tool Selection Through AHP and Simulation. International Journal of Production Research, 45(9): 2029-2050.
  • Ayağ, Z. ve Özdemir, R.G. 2006. A fuzzy AHP Approach to Evaluating Machine Tool Alternatives. Journal of Intelligent Manufacturing, 17: 179-190.
  • Ayağ, Z.,ve Özdemir, R. G. 2011. An Intelligent Approach to Machine tool Selection through Fuzzy Analytic Network Process. Journal of Intelligent Manufacturing, 22(2): 136-177.
  • Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. ve Şahin, C. 2013. Integrating Fuzzy DEMATEL and Fuzzy Hierarchical TOPSIS Methods For Truck Selection. Expert Systems With Applications, 40: 899-907
  • Büyüközkan, G.,Çifçi G. 2012. A Novel Hybrid MCDM Approach Based On Fuzzy DEMATEL, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Supplier. Expert Systems With Applications, 39(3): 3000-3011.
  • Chang, C.W., Wu, C.R., Lin, C.T. ve Chen H.C. 2007. An Application of AHP and Sensitivity Analysis for Selecting The Best Slicing Machine. Computers & Industrial Engineering, 52: 296–307.
  • Chen, L. Y. ve Wang, T. C. 2009. Optimizing Partners’ Choice in IS/IT Outsourcing Projects: The Strategic Decision of Fuzzy VIKOR. International Journal of Production Economics, 120: 233-242.
  • Çakır, S. 2015. An Integrated Approach to Machine Selection Problem Using Fuzzy SMART-Fuzzy Weighted Axiomatic Design. Journal of Intelligent Manufacturing, DOI 10.1007/s10845-015-1189-3
  • Çimren, E., Çatay, B. ve Budak, E. 2007. Development of a Machine Tool Selection System Using AHP. International Journal of Advanced Manufacturing Technology, 35: 363-376.
  • Dağdeviren, M. 2008. Decision Making in Equipment Selection: An Integrated Approach with AHP and PROMETHEE. Journal of Intelligent Manufacturing, 19: 397–406.
  • Dalalah, D., Hayajneh, M. ve Batieha, F. 2011. A Fuzzy Multi-Critera Decision Making Model for Supplier Selection. Expert Systems with Applications, 38: 8834-8391.
  • Duran, O. ve Aguilo, J. 2008. Computer-aided Machine-Tool Selection Based on a Fuzzy-AHP Approach, Expert Systems with Applications. 34: 1787-1794.
  • Ertuğrul, İ. 2007. Bulanık Analitik Hiyerarşi Süreci ve Bir Tekstil İşletmesinde Makine Seçim Problemine Uygulanması, H.Ü. İİBF Dergisi, 25(1), 171-192.
  • Jassbi, J., Mohamadnejad, F. ve Nasrollahzadeh, H. 2011. A Fuzzy DEMATEL Framework For Modeling Cause and Effect Relationships of Strategy Map. Expert Systems with Applications, 38: 5967–5973.
  • Karim, R. ve Karmaker C.L. 2016. Machine Selection by AHP and TOPSIS Methods. American Journal of Industrial Engineering, 4(1): 7-13.
  • Kaya, İ., Kılınç, M.S. ve Çevikcan, E. 2007. Makine-Teçhizat Seçim Probleminde Bulanık Karar Verme Süreci. Mühendis ve Makina, 49(576): 8-14.
  • Kaya, T. ve Kahraman, C. 2010. Multicriteria Renewable Energy Planning Using an Integrated Fuzzy VIKOR & AHP Methodology: The Case of İstanbul”, Energy, 35(6): 2517-2527.
  • Keung, K. W., Ip, W. H. ve Lee, T. C. 2001. A Genetic Algorithm Approach to the Multiple Machine tool Selection Problem. Journal of Intelligent Manufacturing, 12(4), 331-342.
  • Li, R.J. 1999. Fuzzy Method in Group Decision Making. Computers and Mathematics with Applications, 38(1): 91-101.
  • Lin, C.J. ve Wu, W.W. 2008. A Causal Analytical Method For Group Decision-Making Under Fuzzy Environment. Expert Systems with Applications, 34(1): 205-213.
  • Lin, Z.C. ve Yang, C.B. 1996. Evaluation of machine selection by the AHP method. Journal of Materials Processing Technology, 57: 253-258.
  • Moeinzadeh, P. ve Hajfathaliha, A. 2009. A Combined Fuzzy Decision Making Approach to Supply Chain Risk Assessment. World Academy of Science, Engineering and Technology, (60): 519-535.
  • Mishra, S.P., Tiwari, M.K.. ve Lashkari, R. S. 2006. A Fuzzy Goal-Programming Model of Machine Tool Selection and Operation Allocation Problem in FMS: A Quick Converging Simulated Annealing-Based Approach. International Journal of Production Research, 44(1): 43-76.
  • Opricovic, S. 2011. Fuzzy VIKOR with an Application to Water Resources Planning. Expert Systems with Applications, 38: 12983–12990.
  • Opricovic, S. ve Tzeng, G.H. 2004. Compromise solution by MCDM methods: A Comparative Analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156: 445–455.
  • Opricovic, S. ve Tzeng, G.H. 2007. Extended VIKOR Method in Comparison with Outranking Methods. European Journal of Operational Research, 178: 514–529.
  • Organ, A. 2013. Bulanık Dematel Yöntemiyle Makine Seçimini Etkileyen Kriterlerin Değerlendirilmesi. Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi, 22 (1): 157-172.
  • Önüt, S., Kara, S.S. ve Efendigil, T. 2008. A hybrid fuzzy MCDM approach to machine tool selection. Journal of Intelligent Manufacturing, 19: 443-453.
  • Özgen, A., Tuzkaya, G., Tuzkaya, U. R. ve Özgen, D. 2011. A Multi-Criteria Decision Making Approach for Machine Tool Selection Problem in a Fuzzy Environment. International Journal of Computational Intelligence Systems, 4(4): 431-445.
  • Perçin S. 2012. Bulanık AHS ve TOPSIS Yaklaşımının Makine-Teçhizat Seçimine Uygulanması. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21: 169-184.
  • Rai, R., Kameshwaran, S. ve Tiwari, M. K. 2002. Machine–tool Selection and Operation Allocation in FMS: Solving a Fuzzy Goal-Programming Model Using a Genetic Algorithm. International Journal of Production Research, 40(3): 641-665.
  • Samvedi, A., Jain, V. ve Chan, F. T. S. 2012. An Integrated Approach for Machine Tool Selection Using Fuzzy Analytical Hierarchy Process and Grey Relational Analysis. International Journal of Production Research, 50(12): 3211-3221.
  • Sun, S. 2002. Assessing Computer Numerical Control Machines Using Data Envelopment Analysis. International Journal of Production Research, 40(9): 2011-2039.
  • Tabucanon, M. T., Batanov, D. N. ve Verma, D. K. 1994. Intelligent Decision Support System (DSS) for the Selection Process of Alternative Machines for Flexible Manufacturing Systems (FMS). Computers in Industry, 25: 131-143.
  • Taha, Z. ve Rostam, S. 2011. A hybrid fuzzy AHP-PROMETHEE Decision Support System for Machine Tool Selection in Flexible Manufacturing Cell. Journal of Intelligent Manufacturing, 23:2137–2149.
  • Tuzkaya, G., Gülsün, B., Kahraman, C. ve Özgen, D. 2010. An integrated Fuzzy Multi-Criteria Decision Making Methodology for Material Handling Equipment Selection Problem and an Application. Expert Systems with Applications, 37: 2853–2863.
  • Tzeng, G. H., Chiang, C. H., ve Li, C. W. 2007. Evaluating Intertwined Effects in Elearning programs: A Novel Hybrid MCDM Model Based on Factor Analysis and DEMATEL. Expert Systems with Applications, 32(4), 1028–1044.
  • Wang, T. Y., Shaw, C. F. ve Chen, Y. L. 2000. Machine Selection in Flexible Manufacturing Cell: A Fuzzy Multiple Attribute Decision Making Approach. International Journal of Production Research, 38: 2079–2097.
  • Wu, H.,Chen, H. K., Shieh, J. 2010. Evaluating Performance Criteria of Employment Service Outreach Program Personnel by DEMATEL Method. Expert System with Applications, 37:5219–5223.
  • Wu, H. H. ve Tsai Y. N. 2011. An integrated approach of AHP and DEMATEL Methods in Evaluating the Criteria of Auto Spare Parts İndustry. International Journal of Systems Science, 1-11.
  • Yurdakul, M. 2004. AHP as a Strategic Decision-Making Tool to Justify Machine Tool Selection. Journal of Materials Processing Technology, 146: 365-376.
  • Yurdakul, M. ve İç, Y.T. 2009. Analysis of the Benefit Generated by Using Fuzzy Numbers in a TOPSIS Model Developed for Machine Tool Selection Problems. Journal of Materials Processing Technology, 209: 310–317.

Application of Integrated Fuzzy DEMATEL-Fuzzy VIKOR Approach to Machine Selection Problem

Yıl 2017, Cilt: 12 Sayı: 48, 249 - 256, 31.10.2017

Öz

Machine selection issue is a widely important decision problem from the point of production planning in operations. Because of the necessity of considering together various criteria that influencing production speed, costs, capacity and productivity in the process of selecting proper machine, there is a need to an effective decision making tool for machine selection problem. Multi-criteria decision-making (MCDM) techniques that come to the fore with its applicability in many areas can be used as an efficient solving tool in this matter. The main purpose of this study is searching a solution for a company located in the natural stone industry through the use of MCDA techniques. For this aim, fuzzy MCDM approach that takes into account uncertainties of the decision process, an integrated Fuzzy DEMATEL-Fuzzy VIKOR method has been applied to machine selection problem. The criteria determined in accordance with the literature and the structure of the decision problem is primarily evaluated through the opinions of decision makers that consist of managers and engineers in the company. In the light of obtained data, the weights of criteria are acquired by determining the relations among criteria via Fuzzy DEMATEL method. Later, it is provided to select most appropriate marble cutting machine between three alternatives for the related company by applying Fuzzy VIKOR method.

Kaynakça

  • Agdaie, M.H., Zolfani, S.H. ve Zavadskas, E.K. 2013. Decision Making in Machine Tool Selection: An İntagrated Approach With SWARA and COPRAS-G Methods. Engineering Economics, 24(1): 5-17.
  • Arslan, M.Ç., Çatay, B. ve Budak, E. 2004. A Decision Support System For Machine Tool Selection. Journal of Manufacturing Technology Management. 15(1): 101-109.
  • Atmani, A. ve Lashkari, R. S. 1998. A model of Machine-tool Selection and Operation Allocation in FMS. International Journal of Production Research, 36(5): 1339-1349.
  • Ayağ, Z. 2007. A Hybrid Approach to Machine Tool Selection Through AHP and Simulation. International Journal of Production Research, 45(9): 2029-2050.
  • Ayağ, Z. ve Özdemir, R.G. 2006. A fuzzy AHP Approach to Evaluating Machine Tool Alternatives. Journal of Intelligent Manufacturing, 17: 179-190.
  • Ayağ, Z.,ve Özdemir, R. G. 2011. An Intelligent Approach to Machine tool Selection through Fuzzy Analytic Network Process. Journal of Intelligent Manufacturing, 22(2): 136-177.
  • Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. ve Şahin, C. 2013. Integrating Fuzzy DEMATEL and Fuzzy Hierarchical TOPSIS Methods For Truck Selection. Expert Systems With Applications, 40: 899-907
  • Büyüközkan, G.,Çifçi G. 2012. A Novel Hybrid MCDM Approach Based On Fuzzy DEMATEL, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Supplier. Expert Systems With Applications, 39(3): 3000-3011.
  • Chang, C.W., Wu, C.R., Lin, C.T. ve Chen H.C. 2007. An Application of AHP and Sensitivity Analysis for Selecting The Best Slicing Machine. Computers & Industrial Engineering, 52: 296–307.
  • Chen, L. Y. ve Wang, T. C. 2009. Optimizing Partners’ Choice in IS/IT Outsourcing Projects: The Strategic Decision of Fuzzy VIKOR. International Journal of Production Economics, 120: 233-242.
  • Çakır, S. 2015. An Integrated Approach to Machine Selection Problem Using Fuzzy SMART-Fuzzy Weighted Axiomatic Design. Journal of Intelligent Manufacturing, DOI 10.1007/s10845-015-1189-3
  • Çimren, E., Çatay, B. ve Budak, E. 2007. Development of a Machine Tool Selection System Using AHP. International Journal of Advanced Manufacturing Technology, 35: 363-376.
  • Dağdeviren, M. 2008. Decision Making in Equipment Selection: An Integrated Approach with AHP and PROMETHEE. Journal of Intelligent Manufacturing, 19: 397–406.
  • Dalalah, D., Hayajneh, M. ve Batieha, F. 2011. A Fuzzy Multi-Critera Decision Making Model for Supplier Selection. Expert Systems with Applications, 38: 8834-8391.
  • Duran, O. ve Aguilo, J. 2008. Computer-aided Machine-Tool Selection Based on a Fuzzy-AHP Approach, Expert Systems with Applications. 34: 1787-1794.
  • Ertuğrul, İ. 2007. Bulanık Analitik Hiyerarşi Süreci ve Bir Tekstil İşletmesinde Makine Seçim Problemine Uygulanması, H.Ü. İİBF Dergisi, 25(1), 171-192.
  • Jassbi, J., Mohamadnejad, F. ve Nasrollahzadeh, H. 2011. A Fuzzy DEMATEL Framework For Modeling Cause and Effect Relationships of Strategy Map. Expert Systems with Applications, 38: 5967–5973.
  • Karim, R. ve Karmaker C.L. 2016. Machine Selection by AHP and TOPSIS Methods. American Journal of Industrial Engineering, 4(1): 7-13.
  • Kaya, İ., Kılınç, M.S. ve Çevikcan, E. 2007. Makine-Teçhizat Seçim Probleminde Bulanık Karar Verme Süreci. Mühendis ve Makina, 49(576): 8-14.
  • Kaya, T. ve Kahraman, C. 2010. Multicriteria Renewable Energy Planning Using an Integrated Fuzzy VIKOR & AHP Methodology: The Case of İstanbul”, Energy, 35(6): 2517-2527.
  • Keung, K. W., Ip, W. H. ve Lee, T. C. 2001. A Genetic Algorithm Approach to the Multiple Machine tool Selection Problem. Journal of Intelligent Manufacturing, 12(4), 331-342.
  • Li, R.J. 1999. Fuzzy Method in Group Decision Making. Computers and Mathematics with Applications, 38(1): 91-101.
  • Lin, C.J. ve Wu, W.W. 2008. A Causal Analytical Method For Group Decision-Making Under Fuzzy Environment. Expert Systems with Applications, 34(1): 205-213.
  • Lin, Z.C. ve Yang, C.B. 1996. Evaluation of machine selection by the AHP method. Journal of Materials Processing Technology, 57: 253-258.
  • Moeinzadeh, P. ve Hajfathaliha, A. 2009. A Combined Fuzzy Decision Making Approach to Supply Chain Risk Assessment. World Academy of Science, Engineering and Technology, (60): 519-535.
  • Mishra, S.P., Tiwari, M.K.. ve Lashkari, R. S. 2006. A Fuzzy Goal-Programming Model of Machine Tool Selection and Operation Allocation Problem in FMS: A Quick Converging Simulated Annealing-Based Approach. International Journal of Production Research, 44(1): 43-76.
  • Opricovic, S. 2011. Fuzzy VIKOR with an Application to Water Resources Planning. Expert Systems with Applications, 38: 12983–12990.
  • Opricovic, S. ve Tzeng, G.H. 2004. Compromise solution by MCDM methods: A Comparative Analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156: 445–455.
  • Opricovic, S. ve Tzeng, G.H. 2007. Extended VIKOR Method in Comparison with Outranking Methods. European Journal of Operational Research, 178: 514–529.
  • Organ, A. 2013. Bulanık Dematel Yöntemiyle Makine Seçimini Etkileyen Kriterlerin Değerlendirilmesi. Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi, 22 (1): 157-172.
  • Önüt, S., Kara, S.S. ve Efendigil, T. 2008. A hybrid fuzzy MCDM approach to machine tool selection. Journal of Intelligent Manufacturing, 19: 443-453.
  • Özgen, A., Tuzkaya, G., Tuzkaya, U. R. ve Özgen, D. 2011. A Multi-Criteria Decision Making Approach for Machine Tool Selection Problem in a Fuzzy Environment. International Journal of Computational Intelligence Systems, 4(4): 431-445.
  • Perçin S. 2012. Bulanık AHS ve TOPSIS Yaklaşımının Makine-Teçhizat Seçimine Uygulanması. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21: 169-184.
  • Rai, R., Kameshwaran, S. ve Tiwari, M. K. 2002. Machine–tool Selection and Operation Allocation in FMS: Solving a Fuzzy Goal-Programming Model Using a Genetic Algorithm. International Journal of Production Research, 40(3): 641-665.
  • Samvedi, A., Jain, V. ve Chan, F. T. S. 2012. An Integrated Approach for Machine Tool Selection Using Fuzzy Analytical Hierarchy Process and Grey Relational Analysis. International Journal of Production Research, 50(12): 3211-3221.
  • Sun, S. 2002. Assessing Computer Numerical Control Machines Using Data Envelopment Analysis. International Journal of Production Research, 40(9): 2011-2039.
  • Tabucanon, M. T., Batanov, D. N. ve Verma, D. K. 1994. Intelligent Decision Support System (DSS) for the Selection Process of Alternative Machines for Flexible Manufacturing Systems (FMS). Computers in Industry, 25: 131-143.
  • Taha, Z. ve Rostam, S. 2011. A hybrid fuzzy AHP-PROMETHEE Decision Support System for Machine Tool Selection in Flexible Manufacturing Cell. Journal of Intelligent Manufacturing, 23:2137–2149.
  • Tuzkaya, G., Gülsün, B., Kahraman, C. ve Özgen, D. 2010. An integrated Fuzzy Multi-Criteria Decision Making Methodology for Material Handling Equipment Selection Problem and an Application. Expert Systems with Applications, 37: 2853–2863.
  • Tzeng, G. H., Chiang, C. H., ve Li, C. W. 2007. Evaluating Intertwined Effects in Elearning programs: A Novel Hybrid MCDM Model Based on Factor Analysis and DEMATEL. Expert Systems with Applications, 32(4), 1028–1044.
  • Wang, T. Y., Shaw, C. F. ve Chen, Y. L. 2000. Machine Selection in Flexible Manufacturing Cell: A Fuzzy Multiple Attribute Decision Making Approach. International Journal of Production Research, 38: 2079–2097.
  • Wu, H.,Chen, H. K., Shieh, J. 2010. Evaluating Performance Criteria of Employment Service Outreach Program Personnel by DEMATEL Method. Expert System with Applications, 37:5219–5223.
  • Wu, H. H. ve Tsai Y. N. 2011. An integrated approach of AHP and DEMATEL Methods in Evaluating the Criteria of Auto Spare Parts İndustry. International Journal of Systems Science, 1-11.
  • Yurdakul, M. 2004. AHP as a Strategic Decision-Making Tool to Justify Machine Tool Selection. Journal of Materials Processing Technology, 146: 365-376.
  • Yurdakul, M. ve İç, Y.T. 2009. Analysis of the Benefit Generated by Using Fuzzy Numbers in a TOPSIS Model Developed for Machine Tool Selection Problems. Journal of Materials Processing Technology, 209: 310–317.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Bölüm Makaleler
Yazarlar

Cansu Gök Kısa

Selçuk Perçin

Yayımlanma Tarihi 31 Ekim 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 12 Sayı: 48

Kaynak Göster

APA Gök Kısa, C., & Perçin, S. (2017). Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması. Yaşar Üniversitesi E-Dergisi, 12(48), 249-256.
AMA Gök Kısa C, Perçin S. Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması. Yaşar Üniversitesi E-Dergisi. Ekim 2017;12(48):249-256.
Chicago Gök Kısa, Cansu, ve Selçuk Perçin. “Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması”. Yaşar Üniversitesi E-Dergisi 12, sy. 48 (Ekim 2017): 249-56.
EndNote Gök Kısa C, Perçin S (01 Ekim 2017) Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması. Yaşar Üniversitesi E-Dergisi 12 48 249–256.
IEEE C. Gök Kısa ve S. Perçin, “Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması”, Yaşar Üniversitesi E-Dergisi, c. 12, sy. 48, ss. 249–256, 2017.
ISNAD Gök Kısa, Cansu - Perçin, Selçuk. “Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması”. Yaşar Üniversitesi E-Dergisi 12/48 (Ekim 2017), 249-256.
JAMA Gök Kısa C, Perçin S. Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması. Yaşar Üniversitesi E-Dergisi. 2017;12:249–256.
MLA Gök Kısa, Cansu ve Selçuk Perçin. “Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması”. Yaşar Üniversitesi E-Dergisi, c. 12, sy. 48, 2017, ss. 249-56.
Vancouver Gök Kısa C, Perçin S. Bütünleşik Bulanık DEMATEL-Bulanık VIKOR Yaklaşımının Makine Seçimi Problemine Uygulanması. Yaşar Üniversitesi E-Dergisi. 2017;12(48):249-56.