Çok Kriterli Karar Verme Problemlerinde Duyarlılık Analizi

Bu çalışmanın amacı, çok kriterli karar verme (ÇKKV) yöntemlerinin uygulanmasında kullanılan çalışmalar için bir kararlılık ve duyarlılık modeli önermektir. Bu kapsamda kararlılık ve duyarlılık analizi için “kriter ağırlığının varyasyonuna dayalı duyarlılık analizi, sıra ters çevirme özelliğine dayalı duyarlılık analizi ve farklı sıralama metotlarından elde edilen sonuçlar ile karşılaştırma analizi” adımlarının birlikte kullanılması önerilmiştir. Metodun uygulama kısmında alternatif olarak Kırılgan Beşli ülkeleri, bu ülkelere ait işsizlik oranı, devlet bütçesi, GSYİH büyümesi, enflasyon, cari hesap dengesi, risk primi kriter olarak kullanılmıştır. Kriterler MEREC ile ağırlıklandırılmış, alternatiflerin sıralanması ise WISP ile gerçekleştirilmiştir. Metodun uygulama safhasında 22 senaryo üzerinden kriterlere atanan farklı ağırlıklar ile modelin ağırlık katsayılarındaki değişikliklere duyarlı olduğu bulunmuştur. Modelin sıra ters çevirme adımında oluşturulan 4 farklı senaryo üzerinden modelin dinamik bir ortamda geçerli sonuçlar sağladığı görülmüştür. MEREC-WISP tabanlı modelin güvenilirliği için PIV, CoCoSo, COPRAS, WEDBA, TOPSIS ve SAW gibi yaygın olarak kullanılan bazı yöntemlerle bir sıralama karşılaştırması yapılmış ve sonuçların yüksek korelasyona sahip olduğu görülmüştür.

Sensitivity Analysis in Multi-Criterion Decision-Making Problems

The aim of this study is to propose a model of stability and sensitivity for the studies used in the implementation of multi-criteria decision making (MCDM). In this context, it is proposed to use the steps "sensitivity analysis based on the variation of criterion weight, sensitivity analysis based on sequence reversal feature and comparison analysis with results from different sorting methods" for stability and sensitivity analysis. In the implementation part of the method, the Fragile Five countries were used as criteria for the unemployment rate, state budget, GDP growth, inflation, current account balance, risk premium for these countries. The criteria were weighted with MEREC and the ordering of alternatives was carried out with WISP. In the application phase of the method, it was found that the model was sensitive to changes in weight coefficients with different weights assigned to criteria over 22 scenarios. It has been observed that the model provides valid results in a dynamic environment through 4 different scenarios created in the sequence inversion step of the model. For the reliability of the MEREC-WISP-based model, a ranking comparison was made with some commonly used methods such as PIV, CoCoSo, COPRAS, WEDBA, TOPSIS and SAW and the results were found to have a high correlation.

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