Publication: Kararsız Bulanık Çkkv Yaklaşımı İle E-atık Toplama Kutuları İçin Cbs Tabanlı Yer Seçimi
Abstract
Teknolojinin gelişimine ve farklı alanlara yayılmasına bağlı olarak teknolojik alet kullanımı son yıllarda hızla artmaktadır. Kullanım ömrünü tamamlayan teknolojik aletler ise elektronik atık adı verilen atık türünün çoğalmasına sebep olmaktadır. İçerdikleri zararlı maddeler sebebiyle geri dönüşümü veya bertarafı yetkili kuruluşlar tarafından kontrollü şekilde yapılamadığı takdirde e-atıklar havaya, toprağa ve suya karışarak insan sağlığını tehdit etmektedir. Bunun yanı sıra e-atıklar içerdikleri değerli madenler sebebiyle geri dönüşümü ile ekonomiye katkı sağlamaktadır. Resmi Gazete'de yayımlanan Atık Elektrikli ve Elektronik Eşyaların Kontrolü Yönetmeliğince bu atıklar 6 grupta incelenmektedir. Bu çalışmada Çevre, Şehircilik ve İklim Değişikliği Bakanlığı tarafından, 3. ve 4. kategoride yer alan elektrikli ve elektronik atıkların toplanmasında 2015 yılında yetkilendirilmiş kuruluş olan Türkiye Bilişim Sanayicileri Derneği'nin sorumlu olduğu e-atık kutuları için Samsun iline bağlı Atakum ilçesinde en uygun yerin belirlenmesi amaçlanmaktadır. Bu doğrultuda öncelikle alanında uzman beş kişinin desteği ve literatürdeki çalışmalar doğrultusunda e-atık kutularının konumlandırılmasında önem arz eden dokuz kriter belirlenmiştir. Ardından bu kriterler Kararsız Bulanık SWARA yöntemi ile ağırlıklandırılmıştır. Sonrasında Coğrafi Bilgi Sistemleri (CBS) yardımıyla veri setleri oluşturulup, her bir kriter için haritalar elde edilmiştir. Haritalar oluşturulurken Öklid Mesafe Analizi ve Kernel Yoğunluk Analizi kullanılmıştır. Akabinde haritalar 0 ile 1 arasında normalize edilmiş ve kriter ağırlıkları dikkate alınarak ağırlıklı toplam yöntemi ile uygunluk haritası oluşturulmuştur. Bu harita ile e-atık toplama kutuları için alternatif noktalar elde edilmiştir. Elde edilen alternatif noktalar TOPSIS yöntemi ile sıralanmış ve son aşamada kriter ağırlıklarındaki değişimin alternatiflerin sıralamasını nasıl etkilediğini görebilmek adına iki farklı senaryo ile duyarlılık analizi yapılmıştır.
Due to the development of technology and its spread to different areas, the use of technological devices has been increasing rapidly in recent years. Technological devices that have completed their useful life cause an increase in the type of waste called electronic waste. E-waste threatens human health by mixing with air, soil and water if its recycling or disposal cannot be carried out in a controlled manner by authorized institutions due to the harmful substances they contain. On the other hand, e-waste contributes to the economy by recycling due to the precious metals they contain. According to the Regulation on the Control of Waste Electrical and Electronic Equipment published in the Official Gazette, these wastes are examined in 6 groups. In this study, it is aimed to determine the most suitable locations in Atakum district of Samsun province for e-waste bins, which are responsible for the Turkish Informatics Industry Association, which is the organization authorized in 2015 by the Ministry of Environment, Urbanization and Climate Change to collect electrical and electronic waste in the 3rd and 4th categories. In this regard, first of all, with the support of five leading experts and in line with studies in the literature, nine criteria that are important in positioning e-waste bins were determined. Then, these criteria were weighted with the Hesitant Fuzzy SWARA method. Afterwards, data sets were created with the help of Geographic Information Systems (GIS) and maps were obtained for each criterion. Euclidean Distance and Kernel Density Estimation were used when creating the maps. Subsequently, the maps were normalized between 0 and 1, and a suitability map was created using the weighted sum method, taking into account the criterion weights. Alternative points for e-waste collection bins were obtained with this map. The obtained alternative points were ranked with the TOPSIS method, and in the last part, sensitivity analysis was conducted with two different scenarios in order to see how the change in criteria weights affected the ranking of the alternatives.
Due to the development of technology and its spread to different areas, the use of technological devices has been increasing rapidly in recent years. Technological devices that have completed their useful life cause an increase in the type of waste called electronic waste. E-waste threatens human health by mixing with air, soil and water if its recycling or disposal cannot be carried out in a controlled manner by authorized institutions due to the harmful substances they contain. On the other hand, e-waste contributes to the economy by recycling due to the precious metals they contain. According to the Regulation on the Control of Waste Electrical and Electronic Equipment published in the Official Gazette, these wastes are examined in 6 groups. In this study, it is aimed to determine the most suitable locations in Atakum district of Samsun province for e-waste bins, which are responsible for the Turkish Informatics Industry Association, which is the organization authorized in 2015 by the Ministry of Environment, Urbanization and Climate Change to collect electrical and electronic waste in the 3rd and 4th categories. In this regard, first of all, with the support of five leading experts and in line with studies in the literature, nine criteria that are important in positioning e-waste bins were determined. Then, these criteria were weighted with the Hesitant Fuzzy SWARA method. Afterwards, data sets were created with the help of Geographic Information Systems (GIS) and maps were obtained for each criterion. Euclidean Distance and Kernel Density Estimation were used when creating the maps. Subsequently, the maps were normalized between 0 and 1, and a suitability map was created using the weighted sum method, taking into account the criterion weights. Alternative points for e-waste collection bins were obtained with this map. The obtained alternative points were ranked with the TOPSIS method, and in the last part, sensitivity analysis was conducted with two different scenarios in order to see how the change in criteria weights affected the ranking of the alternatives.
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