Çok Kriterli Karar Verme Yöntemlerini Kullanan Makine-Ekipman Seçim Çalışmalarında Bulanıklığın Sonuçlara Etkisinin İncelenmesi

Bulanıklığın ve belirsizliğin bulunduğu seçim problemlerinde Çok Kriterli Karar Verme (ÇKKV) modellerinde tamsayıların yerine bulanık sayıların kullanılması tavsiye edilmektedir. Literatürde pek çok farklı ÇKKV modeli geliştirilmiş olmasına rağmen, şimdiye kadar tamsayıların yerine bulanıklığın kullanılmasının sağladığı faydayı analiz eden bir yaklaşım geliştirilmemiştir. Bu çalışmada bulanık sayıların kullanılmasının getireceği faydalar literatürde makine-ekipman seçimi çalışmalarında en sık rastlanan Bulanık ÇKKV yöntemleri olan Bulanık Analitik Hiyerarşi Süreci (BAHS) ve Bulanık TOPSIS (BTOPSIS) yöntemleri kullanılarak incelenmiştir. Çalışmada, onaltı adet işleme merkezi ve yedi adet seçim kriteri içeren bir seçim problemi oluşturulmuştur. Bulanık sayılar için tamsayı, üçgen bulanık sayı ve trapez bulanık sayı tipleri kullanılarak seçim probleminde farklı işleme merkezi sıralamaları elde edilmiştir. Sıralamalar arasındaki farklılıklar Spearman’ın Sıra İlişkisi Testi ile analiz edilmiştir. Bulanık sayıların kullanımında oluşan faydanın seviyesini belirlemek için çeşitli senaryolar üretilmiştir.

Analysis of the Benefit Generated by Using Fuzzy Numbers in Multi Criteria Decision Making Models Developed for Machine Tool Selection Studies

Fuzzy numbers instead of crisp ones are recommended to use in Multi Criteria Decision Making Models (MCDM) when fuzziness and incomplete information exist in selection problems. Although many different fuzzy MCDM models are developed in the literature, the benefits provided by using them are not analyzed up to now. In this paper, two most common MCDM approaches, namely Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy TOPSIS (FTOPSIS), are used to determine the benefits provided by using fuzzy numbers in machine tool selection problems. In the paper, a sixteen alternative machining center and seven selection criteria problem is constructed. Using two different fuzzy number types (trapezoidal and triangular) and crisp (non-fuzzy) numbers separate rankings are obtained for the selection problem. The differences in the results are analyzed using Spearman’s Rank Correlation Test. Various scenarios are developed to show the level of benefits in using fuzzy numbers.

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