Buradasınız

BULANIK ANALİTİK HİYERARŞİSÜRECİYÖNTEMİNDE DUYARLILIK ANALİZLERİ: YENİBİR ALTERNATİFİN EKLENMESİ- ENERJİ KAYNAĞININ SEÇİMİ ÜZERİNDE BİR UYGULAMA

SENSITIVITY ANALYSES IN THE FUZZY-AHP APPROACH: ADDING A NEW ALTERNATIVE – ENERGY SOURCE SELECTION EXAMPLE

Journal Name:

Publication Year:

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
Values used to solve the decision making problems constructed the subjects such as decision theory, constructing the decision tree, linear programming and simplex methodology are given readily. Accessing these values in real business life is not easy. These values can be altered in an environment in intense competition and uncertainties in crisis. Decision makers want to know the changes in these values. These evaluations are made with the sensitivity analyses in the aforementioned and the other decision making problems. Because of the fact that Classic and Fuzzy Analytic Hierarchy Processes which are based upon qualitative evaluation with mathematical calculations are used as the decision support tools, sensitivity analyses are necessary with regards to the results.The most important advantage of Classic and Fuzzy Analytic Hierarchy Processes is multi criteria decision making techniques which are used in terms of the evaluations both qualitative and quantitative alters. In this study, the importance levels of the alternatives have been determined through the use of Fuzzy Analytic Hierarchy Processes and then sensitivity analysis which are used in linear programming and simplex methodology are combined with the Fuzzy Analytic Hierarchy Process.
Abstract (Original Language): 
Karar kuramı, karar ağacının oluşturulması, doğrusal programlama ve simpleks yöntemi gibi konularda yazılan örnek karar verme problemlerinde, çözüme ulaşmada kullanılan değerler hazır olarak verilmektedir. Ancak gerçek işletme hayatında bu değerlere ulaşmak kolay değildir. Bu değerlere ulaşmanın zorlukları yanında yoğun rekabetin mevcut bulunduğu ve krizin yarattığı belirsizliklerin eklendiği bir ortamda bu değerler de her an değişebilmektedir. Karar vericiler bu değerlerde meydana gelebilecek değişmelerin çözümü nasıl etkileyeceğini bilmek istemektedirler. Bu değerlendirmeler, yukarıda sözü geçen ve diğer tüm karar verme problemlerinde duyarlılık analizleri ile yapılmaktadır. Verileri kalitatif değerlendirmeye, hesaplamaları ise matematiksel temellere dayanan Klasik ve Bulanık Analitik Hiyerarşi Süreci yöntemleri de birer karar destek aracı olarak kullanıldığından, sonuçlar konusunda duyarlılığının analizine ihtiyaç duyulabilmektedir. Klasik veBulanık Analitik Hiyerarşi Süreci’nin en önemli avantajı hem niteliksel hem deniceliksel değişkenleri değerlendirebilmesi açısından sıklıkla başvurulan çok kriterli karar verme teknikleri olmalarıdır. Bu çalışmada hem niteliksel hem de niceliksel alternatiflerin karşılaştırılmasına imkan sağlayan Bulanık Analitik Hiyerarşi Süreci yöntemi kullanılarak alternatiflerin önem düzeyleri tespit edilmişve bunun ardından genellikle doğrusal programlama ve simpleks yönteminde kullanılan duyarlılık analizleri Bulanık Analitik Hiyerarşi Süreci yöntemine entegre edilmiştir.
15-34

REFERENCES

References: 

Cebeci, U. (2008). “Fuzzy AHP-Based Decision Support System for Selecting ERP
Systems in Textile Industry by Using Balanced Scorecard”. Expert Systems with
Applications. (Baskıda makale)
Chang, C-W. Wu, C-R. Lin, C-T. ve H-C. Chen (2007).“An Application of AHP
and Sensitivity Analysis for Selecting The Best Slicing Machine”. Computers &
Industrial Engineering 52, ss. 296–307
Chatzimouratidis, A.I., P.A. Pilavachi (2008). “Sensitivity Analysis of The
Evaluation of Power Plants Impact on The Living Standard Using The Analytic
Hierarchy Process”. Energy Conversion and Management. 49. ss. 3599–3611
Chen, H., D.F. Kocaoğlu (2008). “Sensitivity Analysis Algorithm for Hierarchical
Decision Models”. European Journal of Operational Research. 185, ss. 266–288.
Çakır, O ve M. S. Canbolat (2008) “A Web-Based Decision Support System for
Multi-Criteria Inventory Classification Using FuzzyAHP Methodology” Expert
Systems with Applications. 35. Ss. 1367–1378
Dağdeviren, M. ve İ. Yüksel (2008) “Developing A Fuzzy Analytic Hierarchy
Process (AHP) Model for Behavior-Based Safety Management” Information
Sciences. 178. ss. 1717–1733
Ertuğrul, İ. ve N. Karakaşoğlu (2009) “Performance Evaluation of Turkish Cement
Firms with Fuzzy Analytic Hierarchy Process and TOPSIS Methods” Expert
Systems with Applications 36. ss. 702–715
Gu, X. ve Q. Zhu (2006) “Fuzzy Multi-Attribute Decision-Making Method Based
On Eigenvector Of Fuzzy Attribute Evaluation Space”. Decision Support Systems.
41 (2), ss.400-410.
Güngör, Z. Serhadlıoğlu, G. ve S. E. Kesen (2009) “A Fuzzy AHP Approach To
Personnel Selection Problem” Applied Soft Computing. 9. ss. 641–646
Halaç, O. (1983) Kantitatif Karar Verme Yöntemleri. İstanbul: Alfa Yayınevi
Heizer, J. Ve B. Render (2006) Operations Management. New Jersey: Prentice Hall
İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi Güz 2008/2
33
Hsu, P-F., C-R. Wu ve Y-T. Li (2008). “Selection ofInfectious Medical Waste
Disposal Firms By Using The Analytic Hierarchy Process and Sensitivity Analysis”.
Waste Management. 28. 1386–1394
Kahraman, C., U. Cebeci ve Da Ruan. (2004) “Multi-Attribute Comparison Of
Catering Service Companies Using Fuzzy AHP: The Case Of Turkey”. International
Journal of Production Economics. 87(2), ss.171-184.
Kulak, O. Ve C. Kahraman (2005) “Fuzzy Multi-Attribute Selection Among
Transportation Companies Using Axiomatic Design AndAnalytic Hierarchy
Process”. Information Sciences. 170 (2-4), ss.191-210.
Lawrence J.A. Ve B.A. Pasternak (2002) Applied Management Science Modeling,
Spreadsheet Analysis, And Communication For Decision Making. New York: John
Wiley& Sons Inc.
Lee, A. H. I. Chen, W-C. ve C-J. Chang (2008a) “A Fuzzy AHP and BSC Approach
for Evaluating Performance of IT Department in the Manufacturing Industry in
Taiwan” Expert Systems with Applications. 34. ss. 96–107
Lee, S. K. Mogi, G. Kim, J. W. ve B. J. Gim (2008b)“Fuzzy Analytic Hierarchy
Process Approach for Assessing National Competitiveness in the Hydrogen
Technology Sector” International Journal of Hydrogen Energy 33. Ss. 6840-6848
Lee, S. K. Mogi, G. ve J-W. Kim (2008c) “The Competitiveness of Korea as A
Developer of Hydrogen Energy Technology: The AHP Approach”. Energy Policy
36. ss. 1284–1291
Leung, L.C. ve D. Cao (2000) “On Consistency And Ranking Of Alternatives In
Fuzzy AHP”. European Journal Of Operational Research. 124(1), ss.102-113.
Levin, R.I., D.S. Rubin, J.P. Stinson Ve E.S. Gardner (1992) Quantitative
Approaches To Management. New York: Mc-Graw Hill.
Naghadehi, M. Z. Mikaeil, R. ve M. Ataei (2008) “The Application of Fuzzy
Analytic Hierarchy Process (FAHP) Approach To Selection of Optimum
Underground Mining Method for Jajarm Bauxite Mine, Iran” Expert Systems with
Applications. (Baskıda makale)
Öztürk, A. (2002) Yöneylem Araştırması. Bursa: Ekin Kitabevi.
Render, B., R.M. Stair Ve M.E. Hanna (2003) Quantitative Analysis For
Management. New Jersey: Prentice Hall.
Sheu, J-B. (2004) “A Hybrid Fuzzy-Based Approach For Identifying Global
Logistics Strategies”. Transportation Research. 40 (1), ss. 39-61.
Aşkın ÖZDAĞOĞLU
34
Taylor, B.W. (2002) Introduction To Management Science. New Jersey: Prentice
Hall.
Tiryaki, F. ve B. Ahlatçıoğlu (2009). “Fuzzy Portfolio Selection Using Fuzzy
Analytic Hierarchy Process” Information Sciences 179. ss. 53–69
Tolga, E., M. L. Demircan ve C. Kahraman (2005) “Operating System Selection
Using Fuzzy Replacement Analysis And Analytic Hierarchy Process”. International
Journal of Production Economics. 97 (1), ss. 89-117.
Tütek H. Ve Ş. Gümüşoğlu (2000) Sayısal Yöntemler Yönetsel Yaklaşım. İstanbul:
Beta Basımevi
Walters, D. (2001) Quantitative Methods For Business. Harlow: Prentice Hall Inc.
Winston, W. L. (2004) Operations Research Applications And Algorithms.
Louiseville: Thomson Brooks/Cole.
Wu, M-C. Lo, Y-F. ve S-H. Hsu (2008) “Fuzzy CBR Technique for Generating
Product Ideas”. Expert Systems with Applications. 34. ss. 530–540.
Yu, C-S. (2002) “A GP-AHP Method For Solving Group Decision-Making Fuzzy
AHP Problems”. Computers & Operations Research. 29 (14), ss. 1969-2001.

Thank you for copying data from http://www.arastirmax.com