STOKASTİK ÇOK KRİTERLİ KARAR VERMEDE İKİ YENİ YÖNTEM: SMAA- GRİ İLİŞKİSEL ANALİZ VE SMAADEMATEL-GRİ İLİŞKİSEL ANALİZ

Karar vermede bazı durumlarda karar vericiler tercihlerini kesin değerlerle belirtemez veya belirtmek istemeyebilirler. Bu gibi durumlarda stokastik verilerle karar vermemize olanak sağlayan Stokastik Çok Kriterli Kabul Edilebilirlik Analizi (SMAA), literatürdeki çalışmalarda etkin bir şekilde uygulanan karar destek araçlarındandır. Gri ilişkisel analiz (GİA) ise deterministik veri ile çalışan çok kriterli karar verme (ÇKKV) problemlerinin çözümünde kullanılan alternatif ve popüler yöntemlerden birisidir. Yapılan çalışmada, SMAA-2 ile GİA ve SMAA-2 ile DEMATEL-GİA yöntemlerini birleştiren iki yeni yöntem, SMAA-GİA ve SMAADEMATEL-GİA önerilmiştir. Önerilen yöntemlerden SMAA-GİA daki amaç, GİA nın belirsiz ve kesin olmayan verilerle başa çıkabilmesini sağlayarak stokastik GİA yı oluşturmak, SMAA-DEMATEL-GİA daki amaç ise, stokastik verilerle, kriterlerin birbirlerine olan etkisini, DEMATEL yöntemi ile karar verme sürecine dâhil edebilmektir. Önerilen yöntemler, hem bir gerçek hayat problemine, hem de literatürdeki ilaç fayda risk analizi problemine uygulanmıştır. Sonuçlar göstermektedir ki, SMAA-GİA ve SMAA-DEMATEL-GİA yöntemleri, GİA ve DEMATEL yöntemlerinin stokastik veri ve rasgele ağırlıklar ile güvenilir ve tutarlı çalışmasını, aynı zamanda kriterlerin bağımsız olmadığı durumlarda da basit, hızlı alternatif bir yöntem olarak uygulanabilmesini mümkün kılmaktadır.

TWO NEW METHOD FOR MULTI CRITERIA STOCHASTIC DECISION MAKING: SMAA-GRA AND SMAA-DEMATEL-GRA

In decision-making in some cases decision makers cannot or do not want to specify preferences with the exact values. To decide with these stochastic data Stochastic Multi-Criteria Acceptability Analysis (SMAA) is an effectively implemented decision support tool. Grey Relational Analysis (GRA) which is working only with deterministic data, is an alternative and a popular method for multi criteria decision making problem. In this study, two new methods SMAA-GRA and SMAA-DEMATEL-GRA are proposed: combination of SMAA-2 and GRA methods and also combination of SMAA-2 and DEMATEL-GRA. The aim of the article is to provide GRA cope with vague and imprecise data in other words, to establish stochastic GRA. And also with DEMATEL we can take into account relationship criteria with each other in decision making process. The proposed methods are applied to both drug benefit risk analysis problem in literature and a real life problem. The study shows that SMAA-GRA and SMAA-DEMATEL-GRA whose results are significant and consistent GRA and DEMATEL methods could be used with ambiguous and arbitrarily distributed data for weights and criteria measurements.

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