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ÇOK ÖLÇÜTLÜ KARAR VERME YÖNTEMLERİ İLE BURSİYER SEÇİMİ: BİR EĞİTİM KURUMUNDA UYGULAMA

Yıl 2012, Cilt: 26 Sayı: 3-4, 259 - 272, 07.04.2012

Öz

Türkiye’de yüksek öğrenim gören öğrencilere yönelik olarak
başta Yüksek Öğrenim Kredi ve Yurtlar Kurumu olmak üzere diğer kamu
kurum ve kuruluşları ile çeşitli özel kişi ve kurumlar tarafından farklı ölçütler
göz önünde bulundurularak burs ve yardım verilmektedir.
Burs ve yardım verilecek öğrencilerin belirlenmesi aşamasında çok
ölçütlü karar verme yöntemlerinden biri olan Analitik Hiyerarşi Sürecinin
kullanılması; hem objektif hem de subjektif değerlendirme ölçütlerini
kullanması, değerlendirmelerin tutarlığını test etmesi, çok sayıdaki ölçüte göre
değerlendirilen alternatiflerin önceliklerini belirlemesi açısından önemli bir rol
oynamaktadır. Çalışmada burs veya yardım alacak öğrencilerin belirlenmesinde
göz önünde bulundurulacak ölçütlerin önceliği Analitik Hiyerarşi Süreci ve
TOPSIS ile saptanmıştır.

Kaynakça

  • Aalami H.A., Moghaddam M.P., Yousefi G.R (2010). Modeling and prioritizing demand response programs in power markets. Electric Power Systems Research, 80:4, 426-435.
  • Ayala, J.G. (2011). Selecting irrigation water pricing alternatives using a multi- methodological approach. Mathematical and Computer Modelling, (basımda).
  • Chang C.W., (2010). Collaborative decision making algorithm for selection of optimal wire saw in photovoltaic wafer manufacture. Journal Of Intelligent Manufacturing, (Basımda).
  • Chen M.S., Lin M.C., Wang C.C., Chang C.A. (2009). Using HCA and TOPSIS approaches in personal digital assistant menu–icon interface design. International Journal of Industrial Ergonomics, 39:5, 689-702.
  • Dağdeviren M., Eren T. (2001). Tedarikçi firma seçiminde analitik hiyerarşi prosesi ve 0-1 hedef programlama yöntemlerinin kullanılması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 16:1-2, 41-52.
  • Demirci, E. Küçük, B. (2007). Bursiyerlerin Analitik Hiyerarşi Prosesi (AHP) Yardımı ile Seçimi. Yöneylem Araştırması ve Endüstri Mühendisliği 27. Ulusal Kongresi, 2-4 Temmuz, İzmir.
  • Evren, R., Ülengin, F., (1992). Yönetimde Çok Amaçlı Karar Verme, İTÜ Yayınları, İstanbul.
  • Fazlollahtabar H. (2010). A subjective framework for seat comfort based on a heuristic multi criteria decision making technique and anthropometry. Applied Ergonomics, 42:1, 16-28.
  • Fazlollahtabar H., Mahdavi I., Ashoori M.T., Kaviani S., Amiri N.M. (2011). A multi-objective decision-making process of supplier selection and order allocation for multi-period scheduling in an electronic market. The International Journal Of Advanced Manufacturing Technology, 52:9- 12, 1039-1052.
  • Hacıköylü B.E. (2006). Analitik Hiyerarşi Karar Verme Süreci İle Anadolu Üniversitesi’nde Beslenme Ve Barınma Yardımı Alacak Öğrencilerin Belirlenmesi. Anadolu Üniversitesi Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, Eskişehir.
  • Han F.Y., Jia X.P., Tan X.S. (2003). Two key support tools for environmentally friendly process optimal synthesis. Computer Aided Chemical Engineering, 15, 1274-1279.
  • Hwang, C.L., Yoon, K., Multiple Attribute Decision Making Methods and Applications. Springer, Berlin Heidelberg, 1981.
  • Işıklar G., Büyüközkan G. (2007). Using a multi-criteria decision making approach to evaluate mobile phone alternatives. Computer Standards & Interfaces, 29:2, 265-274.
  • Joshi R., Banwet, D.K., Shankar R. (2011). A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain. Expert Systems with Applications, 38:8, 10170-10182.
  • Ju, Y.,Wang A. (2012). Emergency alternative evaluation under group decision makers: A method of incorporating DS/AHP with extended TOPSIS. Expert Systems with Applications 39:1, 1315-1323.
  • Kandakoglu A., Çelik M., Akgün İ. (2009). A multi-methodological approach for shipping registry selection in maritime transportation industry. Mathematical and Computer Modelling, 49:3-4, 586-597.
  • Kocaoğlu B., Gülsün B., Tanyaş M. (2011). A SCOR based approach for measuring a benchmarkable supply chain performance. Journal Of Intelligent Manufacturing (Basımda).
  • Kuo Y., Yang T., Cho C., Tseng Y.C. (2008). Using simulation and multi- criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors, Mathematics and Computers in Simulation. 78:1, 40-56.
  • Küçük B., Demirci, E., Keskintürk T. (2008). Bursiyerlerin Genetik Algoritma Tekniği Yardımı ile Seçimi. Yöneylem Araştırması ve Endüstri Mühendisliği 28. Ulusal Kongresi, 30 Haziran -2 Temmuz, İstanbul.
  • Lin, M.C., Wang, C.C., Chen, M.S., Chang C.A. (2008). Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry, 59:1, 17-31.
  • Rao R.V., Davim, J.P. (2006). A decision-making framework model for material selection using a combined multiple attribute decision-making method. The International Journal Of Advanced Manufacturing Technology, 35:7-8, 751-760.
  • Rao R.V. (2006). Machinability evaluation of work materials using a combined multiple attribute decision-making method. The International Journal Of Advanced Manufacturing Technology, 28: 3-4, 221-227.
  • Özcan T., Çelebi N., Esnaf Ş. (2011). Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem. Expert Systems with Applications, 38:8, 9773-9779.
  • Saaty, Thomas L. (1980). The Analytic Hierarchy Process. McGraw-Hill International Book Company, New York.
  • Satapathy B.K., Majumdar A., Tomar B.S. (2010). Optimal design of flyash filled composite friction materials using combined Analytical Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solutions approach. Materials & Design, 31:4, 1937-1944.
  • Sobczak A., Berry D.M. (2007). Distributed priority ranking of strategic preliminary requirements for management information systems in economic organizations. Information and Software Technology, 49:9- 10, 960-984.
  • Soltanmohammadi H., Osanloo M., Bazzazi A.A. (2010). An analytical approach with a reliable logic and a ranking policy for post-mining land-use determination. Land Use Policy, 27, 364-372.
  • Tavana M., Marbini A.H. (2011). A group AHP-TOPSIS framework for human spaceflight mission planning at NASA. Expert Systems with Applications, 38:11, 13588-13603.
  • Tzeng G.H., Lin, C.W., Opricovic, S. (2005). Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy, 33:11, 1373-1383.
  • Wang F., Kang S., Du T., Li F., Qiu R. (2011). Determination of comprehensive quality index for tomato and its response to different irrigation treatments. Agricultural Water Management, 98:8, 1228-1238.
  • Wu C.R., Lin C.T., Lin Y.F. (2009). Selecting the preferable bancassurance alliance strategic by using expert group decision technique. Expert Systems with Applications 36:2, 3623-3629.
  • Yousefi A., Vencheh A.H. (2010). An integrated group decision making model and its evaluation by DEA for automobile industry. Expert Systems with Applications, 37:12, 8543-8556.
  • Zanakis S.H., Solomon A., Wishart N., Dublish S. (1998). Multi-attribute decision making: A simulation comparison of select methods. European Journal of Operational Research, 107:3, 507-529.
Yıl 2012, Cilt: 26 Sayı: 3-4, 259 - 272, 07.04.2012

Öz

Kaynakça

  • Aalami H.A., Moghaddam M.P., Yousefi G.R (2010). Modeling and prioritizing demand response programs in power markets. Electric Power Systems Research, 80:4, 426-435.
  • Ayala, J.G. (2011). Selecting irrigation water pricing alternatives using a multi- methodological approach. Mathematical and Computer Modelling, (basımda).
  • Chang C.W., (2010). Collaborative decision making algorithm for selection of optimal wire saw in photovoltaic wafer manufacture. Journal Of Intelligent Manufacturing, (Basımda).
  • Chen M.S., Lin M.C., Wang C.C., Chang C.A. (2009). Using HCA and TOPSIS approaches in personal digital assistant menu–icon interface design. International Journal of Industrial Ergonomics, 39:5, 689-702.
  • Dağdeviren M., Eren T. (2001). Tedarikçi firma seçiminde analitik hiyerarşi prosesi ve 0-1 hedef programlama yöntemlerinin kullanılması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 16:1-2, 41-52.
  • Demirci, E. Küçük, B. (2007). Bursiyerlerin Analitik Hiyerarşi Prosesi (AHP) Yardımı ile Seçimi. Yöneylem Araştırması ve Endüstri Mühendisliği 27. Ulusal Kongresi, 2-4 Temmuz, İzmir.
  • Evren, R., Ülengin, F., (1992). Yönetimde Çok Amaçlı Karar Verme, İTÜ Yayınları, İstanbul.
  • Fazlollahtabar H. (2010). A subjective framework for seat comfort based on a heuristic multi criteria decision making technique and anthropometry. Applied Ergonomics, 42:1, 16-28.
  • Fazlollahtabar H., Mahdavi I., Ashoori M.T., Kaviani S., Amiri N.M. (2011). A multi-objective decision-making process of supplier selection and order allocation for multi-period scheduling in an electronic market. The International Journal Of Advanced Manufacturing Technology, 52:9- 12, 1039-1052.
  • Hacıköylü B.E. (2006). Analitik Hiyerarşi Karar Verme Süreci İle Anadolu Üniversitesi’nde Beslenme Ve Barınma Yardımı Alacak Öğrencilerin Belirlenmesi. Anadolu Üniversitesi Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, Eskişehir.
  • Han F.Y., Jia X.P., Tan X.S. (2003). Two key support tools for environmentally friendly process optimal synthesis. Computer Aided Chemical Engineering, 15, 1274-1279.
  • Hwang, C.L., Yoon, K., Multiple Attribute Decision Making Methods and Applications. Springer, Berlin Heidelberg, 1981.
  • Işıklar G., Büyüközkan G. (2007). Using a multi-criteria decision making approach to evaluate mobile phone alternatives. Computer Standards & Interfaces, 29:2, 265-274.
  • Joshi R., Banwet, D.K., Shankar R. (2011). A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain. Expert Systems with Applications, 38:8, 10170-10182.
  • Ju, Y.,Wang A. (2012). Emergency alternative evaluation under group decision makers: A method of incorporating DS/AHP with extended TOPSIS. Expert Systems with Applications 39:1, 1315-1323.
  • Kandakoglu A., Çelik M., Akgün İ. (2009). A multi-methodological approach for shipping registry selection in maritime transportation industry. Mathematical and Computer Modelling, 49:3-4, 586-597.
  • Kocaoğlu B., Gülsün B., Tanyaş M. (2011). A SCOR based approach for measuring a benchmarkable supply chain performance. Journal Of Intelligent Manufacturing (Basımda).
  • Kuo Y., Yang T., Cho C., Tseng Y.C. (2008). Using simulation and multi- criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors, Mathematics and Computers in Simulation. 78:1, 40-56.
  • Küçük B., Demirci, E., Keskintürk T. (2008). Bursiyerlerin Genetik Algoritma Tekniği Yardımı ile Seçimi. Yöneylem Araştırması ve Endüstri Mühendisliği 28. Ulusal Kongresi, 30 Haziran -2 Temmuz, İstanbul.
  • Lin, M.C., Wang, C.C., Chen, M.S., Chang C.A. (2008). Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry, 59:1, 17-31.
  • Rao R.V., Davim, J.P. (2006). A decision-making framework model for material selection using a combined multiple attribute decision-making method. The International Journal Of Advanced Manufacturing Technology, 35:7-8, 751-760.
  • Rao R.V. (2006). Machinability evaluation of work materials using a combined multiple attribute decision-making method. The International Journal Of Advanced Manufacturing Technology, 28: 3-4, 221-227.
  • Özcan T., Çelebi N., Esnaf Ş. (2011). Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem. Expert Systems with Applications, 38:8, 9773-9779.
  • Saaty, Thomas L. (1980). The Analytic Hierarchy Process. McGraw-Hill International Book Company, New York.
  • Satapathy B.K., Majumdar A., Tomar B.S. (2010). Optimal design of flyash filled composite friction materials using combined Analytical Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solutions approach. Materials & Design, 31:4, 1937-1944.
  • Sobczak A., Berry D.M. (2007). Distributed priority ranking of strategic preliminary requirements for management information systems in economic organizations. Information and Software Technology, 49:9- 10, 960-984.
  • Soltanmohammadi H., Osanloo M., Bazzazi A.A. (2010). An analytical approach with a reliable logic and a ranking policy for post-mining land-use determination. Land Use Policy, 27, 364-372.
  • Tavana M., Marbini A.H. (2011). A group AHP-TOPSIS framework for human spaceflight mission planning at NASA. Expert Systems with Applications, 38:11, 13588-13603.
  • Tzeng G.H., Lin, C.W., Opricovic, S. (2005). Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy, 33:11, 1373-1383.
  • Wang F., Kang S., Du T., Li F., Qiu R. (2011). Determination of comprehensive quality index for tomato and its response to different irrigation treatments. Agricultural Water Management, 98:8, 1228-1238.
  • Wu C.R., Lin C.T., Lin Y.F. (2009). Selecting the preferable bancassurance alliance strategic by using expert group decision technique. Expert Systems with Applications 36:2, 3623-3629.
  • Yousefi A., Vencheh A.H. (2010). An integrated group decision making model and its evaluation by DEA for automobile industry. Expert Systems with Applications, 37:12, 8543-8556.
  • Zanakis S.H., Solomon A., Wishart N., Dublish S. (1998). Multi-attribute decision making: A simulation comparison of select methods. European Journal of Operational Research, 107:3, 507-529.
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Tamer Eren

Yusuf Alper Abalı Bu kişi benim

Batuhan Safa Kutlu Bu kişi benim

Yayımlanma Tarihi 7 Nisan 2012
Yayımlandığı Sayı Yıl 2012 Cilt: 26 Sayı: 3-4

Kaynak Göster

APA Eren, T., Abalı, Y. A., & Kutlu, B. S. (2012). ÇOK ÖLÇÜTLÜ KARAR VERME YÖNTEMLERİ İLE BURSİYER SEÇİMİ: BİR EĞİTİM KURUMUNDA UYGULAMA. Atatürk Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 26(3-4), 259-272.

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