STOKASTİK ÇOK KRİTERLİ KARAR VERMEDE İKİ YENİ YÖNTEM: SMAA- GRİ İLİŞKİSEL ANALİZ ve SMAA-DEMATEL-GRİ İLİŞKİSEL ANALİZ

Yıl 2015, , 0 - 0, 25.12.2015

Mihrimah Özmen , Emel Kızılkaya Aydoğan

https://doi.org/10.17341/gummfd.24515

Cited By: 4

Öz

Karar vermede bazı durumlarda karar vericiler tercihlerini kesin değerlerle belirtemez veya belirtmek istemezler. Bu gibi stokastik verilerle karar verebilmek için Stokastik çok kriterli kabul edilebilirlik analizi (SMAA) etkili bir şekilde uygulanan bir karar destek aracıdır. Gri ilişkisel analiz (GİA) ise ancak deterministik veri ile çalışan çok amaçlı karar verme problemlerinin çözümünde alternatif ve popüler bir yöntemdir. Bu çalışmada SMAA-2 ile GİA ve SMAA-2 ile DEMATEL-GİA metotlarını birleştiren iki yeni metot SMAA-GİA ve SMAA-DEMATEL-GİA önerilmiştir. Bu makalenin amacı GİA’ nın belirsiz ve kesin olmayan verilerle başa çıkabilmesini sağlamak, başka bir deyişle stokastik GİA’ yı oluşturmaktır. Ayrıca kriterlerin birbirleriyle ilişkisini belirlemeye yarayan DEMATEL ile de kriterlerin birbirlerine olan etkisini stokastik verilerle karar verme sürecine katabilmektir.  Literatürdeki ilaç fayda risk analizi problemine ve Türk havacılık şirketleri hakkında bir vaka çalışmasına hem SMAA-GİA hem de SMAA-DEMATEL-GİA yöntemleri uygulanmıştır. Çalışmamız göstermiştir ki güvenilir ve tutarlı sonuçlar veren SMAA-GİA ve SMAA-DEMATEL-GİA yöntemleri, GİA ve DEMATEL yöntemlerini stokastik veri ve rasgele ağırlıkları ile çalışmasını ve SMAA’ nın da kriterlerin bağımsız olmadığı durumlarda uygulanabilmesini mümkün kılmıştır.

Anahtar Kelimeler

Stokastik Çok Kriterli Kabul Edilebilirlik Analizi, Gri İlişkisel Analiz, DEMATEL

Kaynakça

• Tzeng G H,Huang J J (2011). Multiple Attribute Decision Making Methods and Applications. CRC Press: 1-4.
• Pohekar S D and Ramachandran M (2004). Application of Multi-Criteria Decision Making to Sustainable Energy Planning. A review, Renewable and Sustainable Energy Reviews:365–381.
• Saaty T L (1980). The Analytic Hierarchy Process. McGraw-Hill, New York.
• Tervonen T and Figueira J R (2008). A Survey on Stochastic MulticriteriaAcceptability Analysis Methods. Journal of Multi-Criteria Decision Analysis 15 :1–14.
• Lahdelma R, Hokkanen J and Salminen P (1998). SMAA-Stochastic MultiobjectiveAcceptability Analysis. European Journal of Operational Research, 106: 137–143.
• Charnetski J R (1973). The Multiple Attribute Problem with Partial Information: The Expected Value and Comparative HypervolumeMethods. PhdThesis, University of Texas at Austin.
• Charnetski J R and Soland R M (1978). Multiple-Attribute Decision Making with Partial Information: The Comparative Hypervolume Criterion. Naval Research Logistics Quarterly, 25:279–288.
• Bana e Costa, C.A. (1986). A MulticriteriaDecision Aid Methodology to Deal with Conflicting Situations on TheWeights. European Journal of Operational Research 26, 22–34.
• Figueira J R, Greco S and EhrgottM(eds) (2005). Multiple Criteria Decision Analysis: State of the Art Survey,Springer Sciences Business Media, Inc. New York.
• Lahdelma R and Salminen P (2001). SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making. Operations Research, 49(3):444–454.
• Lahdelma R and Salminen P (2002). Pseudo-criteria VersusLinear Utility Function in Stochastic MulticriteriaAcceptability Analysis. European Journal of Operational Research, 141(2):454–469.
• Lahdelma R and Salminen P (2006). Stochastic MulticriteriaAcceptability Analysis Using the Data Envelopment Model. European Journal of Operational Research, 170(1):241–252.
• Lahdelma R, Miettinen K, and Salminen P (2003). Ordinal Criteria in Stochastic MulticriteriaAcceptability Analysis (SMAA). European Journal of Operational Research, 147(1):117–127.
• Lahdelma R and Salminen P (2009). Prospect Theory and Stochastic MulticriteriaAcceptability Analysis (SMAA). Omega, 37(5):961–971.
• Tervonen T, Figueira J R , Lahdelma R, Dias J A, and Salminen P(2009). A Stochastic Method for Robustness Analysis in Sorting Problems. European Journal of Operational Research,192(1):236–242.
• Okul D, Gencer C, Aydogan E K (2013). A Method Based on SMAA-TOPSIS for Stochastıc Multi-criteria decision making and a real world application. International Journal of Information Technology and Decision Making (accepted paper).
• Tervonen T and Lahdelma R (2007). Implementing Stochastic Multicriteria Acceptability Analysis.European Journal of Operational Research, 178(2):500–513.
• Félix A, Baquerizo A, Santiago J M and Losada M A (2012). Coastal Zone Management with Stochastic Multi-Criteria Analysis. Journal of Environmental Management, vol. 112, pp. 252–266
• Kangas A S, Kangas J, Lahdelma R, and SalminenP(2006). Using SMAA-2 Method with Dependent Uncertainties for Strategic Forest Planning. Forest Policy and Economics, 9:113–125.
• Menou A, Benallou A, Lahdelma R, and SalminenP(2009). Decision Support for Centralizing Cargoat a Moroccan Airport Hub Using Stochastic MulticriteriaSystem of Nanomaterials. Journal of Nanoparticle Research, 11(4):757–766.
• Okul D, Gencer C, Aydogan E K (2013). A Method Based on SMAA-TOPSIS for Stochastıc Multi-criteria decision making and a real world application. International Journal of Information Technology and Decision Making (accepted paper).
• DurbachI and DavisyS(2012). Decision Support for Selecting a Shortlist of Electricity-Saving Options: A Modifed SMAA Approach. Journal of Orion, 28:99-116.
• HokkanenJ,Lahdelma R and Salminen P (1999). A Multiple Criteria Decision Model for Analyzing and Choosing Among Different Development Patterns for the Helsinki Cargo Harbor. Socio-Economic Planning Sciences, 33:1–23.
• Hokkanen J, Lahdelma R and SalminenP(2000). Multicriteria Decision Support in a Technology Competition for Cleaning Polluted Soil in Helsinki. Journal of 60(4):339–348.
• Hokkanen J, Lahdelma R, Miettinen K and Salminen P (1998). Determining the Implementation Order of a General Plan by Using a MulticriteriaMethod. Journal of Multi-Criteria Decision Analysis, 7(5):273–284.
• Kangas J, Hokkanen J, Kangas A, Lahdelma R and Salminen P (2003). Applying Stochastic Multicriteria Acceptability Analysis to Forest Ecosystem Management with Both Cardinal and Ordinal Criteria. Forest Science, 49(6):928–937.
• Rocchi L (2011). Using Stochastic Multi-criteria Acceptability Analysis Methods in SEA: An Application to the Park of Trasimeno (Italy).
• Lahdelma R and Salminen P (2008). Ordinal Measurements with Interval Constraints in the A Process for Siting a Waste Storage Area. In Real-Time and Deliberative Decision Making:Application to Emerging Stressors: 397–414.
• Lahdelma R, Salminen P, Simonen A and HokkanenJ(2001). Choosing a Reparation Method for a Landfill Using the SMAA-O Multicriteria method. In Multiple Criteria Decision Making in theNewMillenium, Lecture Notes in Economics and Mathematical Systems, volume 507,Springer-Verlag, Berlin:380–389.
• S. Makkonen, R. Lahdelma, A.M. Asell, and A. Jokinen. Multicriteria Decision Support in the Liberated Energy Market. Journal of Multi-Criteria Decision Analysis, 12(1):27–42.
• Lahdelma R and Salminen P (2012). The Shape of the Utility or Value Function in Stochastic MulticriteriaAcceptability Analysis. OR Spectrum, 34:785-802.
• Makkonen S, Lahdelma R, Asell A. M. and Jokinen A (2003). MulticriteriaDecision Support in the Liberated Energy Market. Journal of Multi-Criteria Decision Analysis, 12(1):27–42.
• Corrente S, Figueira J R, Greco S (2013).The SMAA-PROMETHEE methods.
• Tervonen T, Barberis G F, Figueira J R and R´odenas M E (2007). Siting a University Kindergarten inMadrid with SMAA-III. Working paper 12/2007 of CEG-IST, Technical University of Lisbon,Portugal.
• Tervonen T, Hakonen H and Lahdelma R (2008). Elevator Planning with Stochastic Multicriteria Acceptability Analysis. Omega, 36(3):352–362.
• Tervonen T, Linkov I, Steevens J, Chappell M, Figueira J R and Merad M (2009). Risk-based Classification System of Nanomaterials. Journal of Nanoparticle Research, 11(4):757–766.
• Tervonen T, Figueira J, Lahdelma R and Salminen P (2004). Modelling MCDA Group Preferencesfor Public Human Resource Management: Evaluating the Quality of Education at the Departmentof Information Technology, the University of Turku (Finland). Research Report 22/2004 ofThe Institute of Systems Engineering and Computers (INESC-Coimbra), Coimbra, Portugal.
• Tervonen T, Hillege H L, Buskens E and Postmus D (2010). A-State-of-the- Art Multi Criteria Model for Drug Benefit-Risk Analysis, Working Report. http://drugis.org/files/tervonen-antidep-SOM-final.pdf.
• Aertsen W, Kint V, Orshoven J and Muys B (2011). Evaluation of Modelling Techniques for Forest Site Productivity Prediction in Contrasting Ecoregions using Stochastic MulticriteriaAcceptability Analysis (SMAA).
• Deng JL. Introduction to grey system.J Grey Syst. 1989;1:1e24.
• Bai, Chunguang, and Joseph Sarkis. "A grey-based DEMATEL model for evaluating business process management critical success factors." International Journal of Production Economics 146.1 (2013): 281-292.
• Baykasoğlu, Adil, et al. "Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection." Expert Systems with Applications 40.3 (2013): 899-907.
• Eroğlu, Ö., 2014. Bakım/Onarım Alternatiflerinin Bulanık Dematel Ve SMAA-2 Yöntemleriyle Değerlendirilmesi, Gazi Üniversitesi, Yüksek Lisans Tezi, Ankara.
• AKSAKAL, Erdem; DAĞDEVİREN, Metin. ANP ve DEMATEL Yöntemleri ile Personel Seçimi Problemine Bütünleşik Bir Yaklaşım. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 2010, 25.4.
• Ju-Long, Deng. "Control problems of grey systems." Systems & Control Letters1.5 (1982): 288-294.
• Deng, Ju-Long. "Introduction to grey system theory." The Journal of grey system 1.1 (1989): 1-24.
• Yeh, Ming‐Feng, and Hung‐Ching Lu. "Evaluating weapon systems based on grey relational analysis and fuzzy arithmetic operations." Journal of the Chinese Institute of Engineers 23.2 (2000): 211-221.
• Song, Qinbao, Martin Shepperd, and Carolyn Mair. "Using grey relational analysis to predict software effort with small data sets." Software Metrics, 2005. 11th IEEE International Symposium. IEEE, 2005.
• He, Rong-Song, and Shun-Fa Hwang. "Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis."Engineering Applications of Artificial Intelligence 20.7 (2007): 980-992.
• Xu, Guoping, et al. "A novel conflict reassignment method based on grey relational analysis (GRA)." Pattern Recognition Letters 28.15 (2007): 2080-2087.
• Jadidi, Omid, et al. "An optimal grey based approach based on TOPSIS concepts for supplier selection problem." International Journal of Management Science and Engineering Management 4.2 (2009): 104-117.
• Özdemir, Ali İhsan, and Mustafa Deste. "Gri İlişkisel Analiz ile Çok Kriterli Tedarikçi Seçimi: Otomotiv Sektöründe Bir Uygulama." Istanbul University Journal of the School of Business Administration 38.2 (2009): 147-156.
• Qian, Wu, and Luyan Li. "Research on Investment Decision-Making of Construction Engineering Projects Based on the Grey Relation Grade."Advanced Science Letters 15.1 (2012): 407-409.
• Wu, Hsin-Hung. "A comparative study of using grey relational analysis in multiple attribute decision making problems." Quality Engineering 15.2 (2002): 209-217.
• Wu, Wei-Wen, and Yu-Ting Lee. "Developing global managers’ competencies using the fuzzy DEMATEL method." Expert systems with applications 32.2 (2007): 499-507.
• Fontela, E., and A. Gabus. "DEMATEL, innovative methods. Report no. 2 structural analysis of the world problematique." Battelle Geneva Research Institute (1974): 67-69.
• Fontela, E., and A. Gabus. "The DEMATEL Observer, DEMATEL 1976 Report. Switzerland, Geneva, Battelle Geneva Research Center. February 5, 2007." (1976).
• Gabus, A., and E. Fontela. "World problems, an invitation to further thought within the framework of DEMATEL." Battelle Geneva Research Center, Geneva, Switzerland (1972).
• Ehrgott M, Figueira J R and Greco S(2010). Trends in Multiple Criteria Decision Analysis, Springer.
• Chan, Lai K., and Ming L. Wu. "Prioritizing the technical measures in quality function deployment." Quality engineering 10.3 (1998): 467-479.
• Aydogan, E. K. (2011). Performance measurement model for Turkish aviation firms using the rough-AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications, 38(4), 3992-3998.